report writing on covid 19 for students

• Report Writing On Covid 19 For Students

Report Writing on COVID-19 for Students

A report, as you know, is a detailed account of a particular event or something that happened. Writing a report on a pandemic such as COVID-19, which shook the whole world, requires a lot of research. You should have a thorough knowledge of the details that have to be included in the report before you start writing one. Check out the following sections to learn what they are and also go through the sample reports to see how to structure your report.

Table of Contents

What to include in a report on covid-19, sample report on covid-19 around the world, sample report on covid-19 in india for students, frequently asked questions on report writing on covid-19.

Before you start writing your report, make sure you understand what the term ‘COVID-19’ refers to and gather all the significant information about it. Since COVID-19 is a pandemic, you have to try and understand the causes, symptoms, difficulties caused by the virus, aftereffects, precautions, aftercure and so on. Once you do this, also explore information about the number of cases reported, number of deaths caused, number of people cured, advancements in the field of medicine, etc. Having a thorough knowledge of these factors can give you a clear idea of what to write and how to structure your report.

While plague, cholera and flu were pandemics of the past, the current COVID-19 pandemic has put the whole world in a fix. With the first case of COVID-19 reported in Wuhan, Hubei Province, China in December of 2019, life on Earth had changed forever. Since then, everybody was locked inside, asked to cover their noses and mouths, wash their hands, keep themselves clean, use sanitisers every time they step out and step back into their houses, eat protein-rich and hygienic food, inhale steam, drink hot water and so on. For many, everything changed with the outbreak of the pandemic. A huge number of people lost their loved ones, some their jobs and some were even disturbed mentally rather than just physically. Life simply switched to a new normal.

The commonly found symptoms were fatigue, severe headaches, common cold, breathing difficulties, reduced oxygen levels, loss of appetite, taste and smell and so on. The government and the medical community continuously asked people to be on their guard, stay indoors and report to the nearest hospitals in case they identify any of the above stated symptoms in themselves or in the people around them.

As of December 2021, around 1 million new cases and around 7500 deaths were reported and the daily moving average of cases rose to 390 in the first week of December. However, with the development of vaccinations by scientists and doctors, the number of cases as well as the number of deaths have been reduced. Still, people have been asked to take precautions even though vaccinations have been administered to most people around the world.

The spread of COVID-19 in India began with the first case being reported in Kerala on January 30, 2020. In a year’s time, more than twenty-eight million people were tested positive for COVID. Around five million people – the highest recorded number of diagnosed cases – were from Maharashtra; the next in line was Karnataka, Kerala and Tamil Nadu with more than two million cases each, followed by Andhra Pradesh with over one million cases.

Owing to the widespread increase in the number of deaths, Prime Minister Narendra Modi announced a nationwide lockdown until further notice. All schools, colleges and offices were closed. Schools, colleges, community halls and convention centers were turned into isolation wards as hospitals were overflowing with patients. Healthcare professionals, along with many volunteers, worked day and night to treat patients and reduce the number of deaths.

After almost a year, vaccinations such as Covishield and Covaxin were launched in India. These vaccines were first administered to people above the age of sixty, followed by people from the age of forty to sixty, above eighteen and then younger kids. Vaccinations were given in two doses with an interval of one and a half to two months in between. With the government making vaccinations mandatory for travel and other purposes, almost all people had taken the vaccinations. A third dose of the vaccine (booster dose) also has been launched. The government has taken efforts to set up multiple vaccination booths in government schools and hospitals. With continuous efforts from the government, medical and police officials, and cooperation from the citizens, India has successfully seen a decrease in the number of cases and deaths, and an increase in the number of recoveries.

What is a report?

A report is an official document presented in writing or print about a particular event or happening.

What are the details to be included in a report on COVID-19?

The details to be included in a report on COVID-19 are as follows.

• Difficulties caused by the virus
• Aftereffects
• Precautions
• Number of cases reported
• Number of deaths caused
• Number of people cured
• Advancements in the field of medicine

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The pandemic has had devastating impacts on learning. What will it take to help students catch up?

Subscribe to the brown center on education policy newsletter, megan kuhfeld , megan kuhfeld senior research scientist - nwea @megankuhfeld jim soland , jim soland assistant professor, school of education and human development - university of virginia, affiliated research fellow - nwea @jsoland karyn lewis , and karyn lewis director, center for school and student progress - nwea @karynlew emily morton emily morton research scientist - nwea @emily_r_morton.

March 3, 2022

As we reach the two-year mark of the initial wave of pandemic-induced school shutdowns, academic normalcy remains out of reach for many students, educators, and parents. In addition to surging COVID-19 cases at the end of 2021, schools have faced severe staff shortages , high rates of absenteeism and quarantines , and rolling school closures . Furthermore, students and educators continue to struggle with mental health challenges , higher rates of violence and misbehavior , and concerns about lost instructional time .

As we outline in our new research study released in January, the cumulative impact of the COVID-19 pandemic on students’ academic achievement has been large. We tracked changes in math and reading test scores across the first two years of the pandemic using data from 5.4 million U.S. students in grades 3-8. We focused on test scores from immediately before the pandemic (fall 2019), following the initial onset (fall 2020), and more than one year into pandemic disruptions (fall 2021).

Average fall 2021 math test scores in grades 3-8 were 0.20-0.27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores were 0.09-0.18 SDs lower. This is a sizable drop. For context, the math drops are significantly larger than estimated impacts from other large-scale school disruptions, such as after Hurricane Katrina—math scores dropped 0.17 SDs in one year for New Orleans evacuees .

Even more concerning, test-score gaps between students in low-poverty and high-poverty elementary schools grew by approximately 20% in math (corresponding to 0.20 SDs) and 15% in reading (0.13 SDs), primarily during the 2020-21 school year. Further, achievement tended to drop more between fall 2020 and 2021 than between fall 2019 and 2020 (both overall and differentially by school poverty), indicating that disruptions to learning have continued to negatively impact students well past the initial hits following the spring 2020 school closures.

These numbers are alarming and potentially demoralizing, especially given the heroic efforts of students to learn and educators to teach in incredibly trying times. From our perspective, these test-score drops in no way indicate that these students represent a “ lost generation ” or that we should give up hope. Most of us have never lived through a pandemic, and there is so much we don’t know about students’ capacity for resiliency in these circumstances and what a timeline for recovery will look like. Nor are we suggesting that teachers are somehow at fault given the achievement drops that occurred between 2020 and 2021; rather, educators had difficult jobs before the pandemic, and now are contending with huge new challenges, many outside their control.

Clearly, however, there’s work to do. School districts and states are currently making important decisions about which interventions and strategies to implement to mitigate the learning declines during the last two years. Elementary and Secondary School Emergency Relief (ESSER) investments from the American Rescue Plan provided nearly $200 billion to public schools to spend on COVID-19-related needs. Of that sum, $22 billion is dedicated specifically to addressing learning loss using “evidence-based interventions” focused on the “ disproportionate impact of COVID-19 on underrepresented student subgroups. ” Reviews of district and state spending plans (see Future Ed , EduRecoveryHub , and RAND’s American School District Panel for more details) indicate that districts are spending their ESSER dollars designated for academic recovery on a wide variety of strategies, with summer learning, tutoring, after-school programs, and extended school-day and school-year initiatives rising to the top.

Comparing the negative impacts from learning disruptions to the positive impacts from interventions

To help contextualize the magnitude of the impacts of COVID-19, we situate test-score drops during the pandemic relative to the test-score gains associated with common interventions being employed by districts as part of pandemic recovery efforts. If we assume that such interventions will continue to be as successful in a COVID-19 school environment, can we expect that these strategies will be effective enough to help students catch up? To answer this question, we draw from recent reviews of research on high-dosage tutoring , summer learning programs , reductions in class size , and extending the school day (specifically for literacy instruction) . We report effect sizes for each intervention specific to a grade span and subject wherever possible (e.g., tutoring has been found to have larger effects in elementary math than in reading).

Figure 1 shows the standardized drops in math test scores between students testing in fall 2019 and fall 2021 (separately by elementary and middle school grades) relative to the average effect size of various educational interventions. The average effect size for math tutoring matches or exceeds the average COVID-19 score drop in math. Research on tutoring indicates that it often works best in younger grades, and when provided by a teacher rather than, say, a parent. Further, some of the tutoring programs that produce the biggest effects can be quite intensive (and likely expensive), including having full-time tutors supporting all students (not just those needing remediation) in one-on-one settings during the school day. Meanwhile, the average effect of reducing class size is negative but not significant, with high variability in the impact across different studies. Summer programs in math have been found to be effective (average effect size of .10 SDs), though these programs in isolation likely would not eliminate the COVID-19 test-score drops.

Figure 1: Math COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) Table 2; summer program results are pulled from Lynch et al (2021) Table 2; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span; Figles et al. and Lynch et al. report an overall effect size across elementary and middle grades. We were unable to find a rigorous study that reported effect sizes for extending the school day/year on math performance. Nictow et al. and Kraft & Falken (2021) also note large variations in tutoring effects depending on the type of tutor, with larger effects for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

Figure 2 displays a similar comparison using effect sizes from reading interventions. The average effect of tutoring programs on reading achievement is larger than the effects found for the other interventions, though summer reading programs and class size reduction both produced average effect sizes in the ballpark of the COVID-19 reading score drops.

Figure 2: Reading COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; extended-school-day results are from Figlio et al. (2018) Table 2; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) ; summer program results are pulled from Kim & Quinn (2013) Table 3; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: While Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span, Figlio et al. and Kim & Quinn report an overall effect size across elementary and middle grades. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

There are some limitations of drawing on research conducted prior to the pandemic to understand our ability to address the COVID-19 test-score drops. First, these studies were conducted under conditions that are very different from what schools currently face, and it is an open question whether the effectiveness of these interventions during the pandemic will be as consistent as they were before the pandemic. Second, we have little evidence and guidance about the efficacy of these interventions at the unprecedented scale that they are now being considered. For example, many school districts are expanding summer learning programs, but school districts have struggled to find staff interested in teaching summer school to meet the increased demand. Finally, given the widening test-score gaps between low- and high-poverty schools, it’s uncertain whether these interventions can actually combat the range of new challenges educators are facing in order to narrow these gaps. That is, students could catch up overall, yet the pandemic might still have lasting, negative effects on educational equality in this country.

Given that the current initiatives are unlikely to be implemented consistently across (and sometimes within) districts, timely feedback on the effects of initiatives and any needed adjustments will be crucial to districts’ success. The Road to COVID Recovery project and the National Student Support Accelerator are two such large-scale evaluation studies that aim to produce this type of evidence while providing resources for districts to track and evaluate their own programming. Additionally, a growing number of resources have been produced with recommendations on how to best implement recovery programs, including scaling up tutoring , summer learning programs , and expanded learning time .

Ultimately, there is much work to be done, and the challenges for students, educators, and parents are considerable. But this may be a moment when decades of educational reform, intervention, and research pay off. Relying on what we have learned could show the way forward.

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The impact of COVID-19 on student experiences and expectations: Evidence from a survey ☆

Esteban m. aucejo.

a Department of Economics, Arizona State University, CEP & NBER, United States of America

Jacob French

b Department of Economics, Arizona State University, United States of America

Maria Paola Ugalde Araya

Basit zafar.

c Department of Economics, University of Michigan, & NBER, United States of America

In order to understand the impact of the COVID-19 pandemic on higher education, we surveyed approximately 1500 students at one of the largest public institutions in the United States using an instrument designed to recover the causal impact of the pandemic on students' current and expected outcomes. Results show large negative effects across many dimensions. Due to COVID-19: 13% of students have delayed graduation, 40% have lost a job, internship, or job offer, and 29% expect to earn less at age 35. Moreover, these effects have been highly heterogeneous. One quarter of students increased their study time by more than 4 hours per week due to COVID-19, while another quarter decreased their study time by more than 5 hours per week. This heterogeneity often followed existing socioeconomic divides. Lower-income students are 55% more likely than their higher-income peers to have delayed graduation due to COVID-19. Finally, we show that the economic and health related shocks induced by COVID-19 vary systematically by socioeconomic factors and constitute key mediators in explaining the large (and heterogeneous) effects of the pandemic.

• • Due to COVID: 13% of students delayed graduation, 40% lost a job, internship, or offer, and 29% expect to earn less at 35.
• • The effects of the pandemic have been highly heterogeneous.
• • Lower-income students are 55% more likely than their higher-income peers to have delayed graduation due to COVID-19.
• • COVID-19's economic and health shocks vary by socioeconomic status and act as key mediators explaining pandemic's effects.

1. Introduction

The disruptive effects of the COVID-19 outbreak have impacted almost all sectors of our society. Higher education is no exception. Anecdotal evidence paints a bleak picture for both students and universities. According to the American Council on Education, enrollment is likely to drop by 15% in the fall of 2020, while at the same time many institutions may have to confront demands for large tuition cuts if classes remain virtual. 1 In a similar vein, students face an increasingly uncertain environment, where financial and health shocks (for example, lack of resources to complete their studies or fear of becoming seriously sick), along with the transition to online learning may have affected their academic performance, educational plans, current labor market participation, and expectations about future employment.

This paper attempts to shed light on the impact of the COVID-19 pandemic on college students. First, we describe and quantify the causal effects of the COVID-19 outbreak on a wide set of students' outcomes/expectations. In particular, we analyze enrollment and graduation decisions, academic performance, major choice, study and social habits, remote learning experiences, current labor market participation, and expectations about future employment. Second, we study how these effects differ along existing socioeconomic divides and whether the pandemic has exacerbated existing inequalities. Finally, we present suggestive evidence on the mechanisms behind the heterogeneous COVID-19 effects by quantifying the relationship between individual-level (financial and health) shocks and students' academic decisions and labor market expectations.

For this purpose, we surveyed about 1500 undergraduate students at Arizona State University (ASU), one of the largest public universities in the United States, in late April 2020. The survey was explicitly designed to not only collect student outcomes and expectations after the onset of the pandemic, but also to recover counterfactual outcomes in the absence of the outbreak. Specifically, the survey asked students about their current experiences/expectations and what those experiences/expectations would have been had it not been for the pandemic. Because we collect information conditional on both states of the world (with the COVID-19 pandemic, and without) from each student , we can directly analyze how each student believes COVID-19 has impacted their current and future outcomes. 2 For example, by asking students about their current GPA in a post-COVID-19 world and their expected GPA in the absence of COVID-19, we can back out the subjective treatment effect of COVID-19 on academic performance. The credibility of our approach depends on: (1) students having well-formed beliefs about outcomes in the counterfactual scenario. This is a plausible assumption in our context since the counterfactual state is a realistic and relevant one - it was the status quo less than two months before the survey, and (2) there being no systematic bias in the reporting of the data - an assumption that is implicitly made when using any survey data. 3

Our findings on academic outcomes indicate that COVID-19 has led to a large number of students delaying graduation (13%), withdrawing from classes (11%), and intending to change majors (12%). Moreover, approximately 50% of our sample separately reported a decrease in study hours and in their academic performance. Predicting the longer-term impact of the pandemic on student achievement is more difficult, but students reported that they expect to take a break from college in the fall 2020 semester at more than twice the rate in previous years. Historically, 28% of students who fail to re-enroll do not return to ASU or another university after 5 years (authors' calculations from ASU first-time freshmen transcript data for the 2012–2014 spring semesters), suggesting that the pandemic may have a lasting impact on the educational achievement of current students. We also find that students report a decreased preference for online instruction as a result of their recent experiences.

As expected, the COVID-19 outbreak also had large negative effects on students' current labor market participation and expectations about post-college labor outcomes. Working students suffered a 31% decrease in their wages and a 37% drop in weekly hours worked, on average. Moreover, around 40% of students lost a job, internship, or a job offer, and 61% reported to have a family member that experienced a reduction in income. The pandemic also had a substantial impact on students' expectations about their labor market prospects post-college. For example, their perceived probability of finding a job before graduation decreased by almost 20%, and their expected earnings when 35 years old (around 15 years from the outbreak) declined by approximately 2.5%. This last finding suggests that students expect the pandemic to have a long-lasting impact on their labor market prospects, which is qualitatively consistent with the literature on graduating during a recession. For instance, Oreopoulos et al. (2012) and Schwandt and von Wachter (2019) find significant reductions in earnings 5 and 10 years after graduation, respectively, and Kahn (2010) finds an even longer-lasting effect on wages. On the other hand, although we are measuring the probability of finding a job before graduating, not unemployment directly, our estimated quantitative effect on students' expectations of finding a job seems to be larger relative to the literature ( Kahn, 2010 ; Altonji et al., 2016 ; and Rothstein, 2020 ).

The data also show that while all subgroups of the population have experienced negative effects due to the outbreak, the size of the effects are heterogeneous. For example, compared to their more affluent peers, lower-income students are 55% more likely to delay graduation due to COVID-19 and are 41% more likely to report that COVID-19 impacted their major choice. Further, COVID-19 nearly doubled the gap between higher- and lower-income students' expected GPA. 4 There also is substantial variation in the pandemic's effect on preference for online learning, with Honors students and males revising their preferences down more than 2.5 times as much as their peers. However, despite appearing to be more disrupted by the switch to online learning, the impact of COVID-19 on Honors students' academic outcomes is consistently smaller than the impact on non-Honors students.

Finally, we evaluate the extent to which mitigating factors associated with more direct economic and health shocks from the pandemic (for example, a family member losing income due to COVID-19, or the expected probability of hospitalization if contracting COVID-19) can explain the heterogeneity in pandemic effects. We find that both types of shock (economic and health) are systematically correlated with students' COVID-19 experiences. For example, the expected probability of delaying graduation due to COVID-19 increases by approximately 25% if either a student's subjective probability of being late on a debt payment in the following 90 days (a measure of financial fragility) or subjective probability of requiring hospitalization conditional on contracting COVID-19 increases by one standard deviation. As expected, the magnitude of health and economic shocks are not homogeneous across the student population. The average of the principal component for the economic and health shocks is about 0.3–0.4 standard deviations higher for students from lower-income families. Importantly, we find that the disparate economic and health impacts of COVID-19 can explain 40% of the delayed graduation gap (as well as a substantial part of the gap for other outcomes) between lower- and higher-income students. This analysis should be viewed as descriptive in nature and not necessarily causal, since omitted factors that are correlated both with the shocks and the outcomes may be driving these relationships.

To our knowledge, this is the first paper to shed light on the effects of COVID-19 on college students' experiences. The treatment effects that we find are large in economic terms. Whether students are overreacting in their response to the COVID-19 shock is not clear. We do find that previous cumulative GPA is a strong predictor of expected semester GPA without COVID-19, suggesting that students' reported expectations are meaningful. However, we know that individuals generally tend to overweight recent experiences ( Malmendier and Nagel, 2016 ; Kuchler and Zafar, 2019 ). Whether students' subjective treatment effects are “correct” in some ex-post sense is beside the point. As long as students are reporting their subjective beliefs without any systematic bias, it is the perceived treatment effects, not actual ones, – regardless of whether they are correct or not – which are fundamental to understanding choices. For example, if students (rightly or wrongly) perceive a negative treatment effect of COVID-19 on the returns to a college degree, this belief will have an impact on their future human capital decisions (such as continuing with their education, choice of major, etc.).

Our results underscore the fact that the COVID-19 shock is likely to exacerbate socioeconomic disparities in higher education. This is consistent with findings regarding the impacts of COVID-19 on K-12 students. Kuhfeld et al. (2020) project that school closures are likely to lead to significant learning losses in math and reading. However, they estimate heterogeneous effects, and conclude that high-performing students are likely to make gains. Likewise, Chetty et al. (2020) find that, post-COVID, student progress on an online math program decreased significantly more in poorer ZIP codes. Our analysis reveals that the heterogeneous economic and health burden imposed by COVID-19 can partially explain these varying impacts. This suggests that by addressing the economic and health impacts imposed by COVID-19, policy makers may be able to prevent COVID-19 from widening existing gaps in higher education.

2.1. Survey

Our data come from an original survey of undergraduate students at Arizona State University (ASU), one of the largest public universities in the United States. Like other higher educational institutions in the US, the Spring 2020 semester started in person. However, in early March during spring break, the school announced that instruction would be transitioned online and that students were advised not to return to campus.

The study was advertised on the My ASU website, accessible only through the student's ASU ID and password. Undergraduate students were invited to participate in an online survey about their experiences and expectations in light of the COVID-19 pandemic, for which they would be paid $10. The study was posted during the second to last week of instruction for the spring semester (April 23rd). Our sample size was constrained by the research funds to 1500 students, and the survey was closed once the desired sample size was reached, which happened within 3 days of posting the survey.

The survey was programmed in Qualtrics. It collected data on students' demographics and family background, their current experiences (both for academic outcomes and non-academic outcomes), and their future expectations. Importantly for the purposes of this study, the survey collected data on what these outcomes/expectations would have been in the counterfactual state, without COVID-19. The survey instrument (with only the relevant sections) can be found here .

2.2. Sample

A total of 1564 respondents completed the survey. 5 90 respondents were ineligible for the study (such as students enrolled in graduate degree programs or diploma programs) and were dropped from the sample. Finally, responses in the 1st and 99th percentile of survey duration were further excluded, leading to a final sample size of 1446. The survey took 38 min to complete, on average (median completion time was 26 min).

The first five columns of Table 1 show how our sample compares with the broader ASU undergraduate population and the average undergraduate student at other large flagship universities (specifically, the largest public universities in each state). Relative to the ASU undergraduate population, our sample has a significantly higher proportion of first-generation students (that is, students with no parent with a college degree), and a smaller proportion of international students. The demographic composition of our sample compares reasonably well with that of students in flagship universities. Our sample is also positively selected in terms of SAT/ACT scores relative to these two populations. The sample may also differ from the student body at other large public schools in that 30% report living on campus, which is not always the norm at other large institutions and may play an important role in how disruptive the pandemic has been. 6

Summary statistics.

Notes: Data in columns (2), (3) and (8) is from IPEDS 2018. The flagship universities are the 4-year public universities with the highest number of undergraduate students in each state. Means for these columns are weighted by total number of undergraduates in each institution. ACT and SAT data are weighted averages of 2018–2015 years from IPEDS. P -value columns show the p -value of a difference in means test between the two columns indicated by the numbers in the heading.

The better performance on admission tests could be explained by the high proportion of Honors students in our sample (22% compared to 18% in the ASU population). The last four columns of Table 1 show how Honors students compare with ASU students and the average college student at a top-10 university. We see that they perform better than the average ASU student (which is expected) and just slightly worse than the average college student at a top-10 university. The share of white Honors students in our sample (60%) is higher than the proportion in the ASU population and much higher than the proportion of white students in the top-10 universities.

Overall, we believe our sample of ASU students is a reasonable representation of students at other large public schools, while the Honors students may provide insight into the experiences of students at more elite Institutions. Though, it is important to acknowledge that elite institutions may have additional resources to address a global pandemic.

3. Analytic framework

We next outline a simple analytic framework that guides the empirical analysis. Let O i ( COVID  – 19) be the potential outcome of individual i associated with COVID-19 treatment. We are interested in the causal impact of COVID-19 on student outcomes:

where the first term on the right-hand side is student i 's outcome in the state of the world with COVID-19, and the second term being student i 's outcome in the state of the world without COVID-19. Recovering the treatment effect at the individual level entails comparison of the individual's outcomes in two alternate states of the world. With standard data on realizations, a given individual is observed in only one state of the world (in our case, COVID –  19 = 1). The alternate outcomes are counterfactual and unobserved. A large econometric and statistics literature studies how to identify these counterfactual outcomes and moments of the counterfactual outcomes (such as average treatment effects) from realized choice data (e.g., Heckman and Vytlacil, 2005 ; Angrist and Pischke, 2009 ; Imbens and Rubin, 2015 ). Instead, the approach we use in this paper is to directly ask individuals for their expected outcomes in both states of the world. From the collected data, we can then directly calculate the individual-level subjective treatment effect. As an example, consider beliefs about end-of-semester GPA. The survey asked students “ What semester-level GPA do you expect to get at the end of this semester ?” This is the first-term on the right-hand side of Eq. (1) . The counterfactual is elicited as follows “ Were it not for the COVID-19 pandemic , what semester-level GPA would you have expected to get at the end of the semester ?”. The difference in the responses to these two questions gives us the subjective expected treatment effect of COVID-19 on the student's GPA. For certain binary outcomes in the survey, we directly ask students for the Δ i . For example, regarding graduation plans, we simply ask a student if the Δ i is positive, negative, or zero: “ How has the COVID-19 pandemic affected your graduation plan ? [ graduate later ; graduation plan unaffected ; graduate earlier ].”

The approach we use in this paper follows a small and growing literature that uses subjective expectations to understand decision-making under uncertainty. Specifically, Arcidiacono et al. (2020) and Wiswall and Zafar (2020) ask college students about their beliefs for several outcomes associated with counterfactual choices of college majors, and estimate the ex-ante treatment effects of college majors on career and family outcomes. Shapiro and Giustinelli (2019) use a similar approach to estimate the subjective ex-ante treatment effects of health on labor supply. There is one minor distinction from these papers: while these papers elicit ex-ante treatment effects, in our case, we look at outcomes that have been observed (for example, withdrawing from a course during the semester) as well as those that will be observed in the future (such as age 35 earnings). Thus, some of our subjective treatment effects are ex-post in nature while others are ex-ante.

The soundness of our approach depends on a key assumption that students have well-formed expectations for outcomes in both the realized state and the counterfactual state. Since the outcomes we ask about are absolutely relevant and germane to students, they should have well-formed expectations for the realized state. In addition, given that the counterfactual state is the one that had been the status quo in prior semesters (and so students have had prior experiences in that state of the world), their ability to have expectations for outcomes in the counterfactual state should not be a controversial assumption. 7 As evidence that students' expectations exhibit meaningful variation, Appendix Fig. A1 shows that previous cumulative GPA is a strong predictor of expected semester GPA with COVID-19.

4. Empirical analysis

4.1. treatment effects.

We start with the analysis of the aggregate-level treatment effects, which are presented in Table 2 . The outcomes are organized in two groups, academic and labor market (see Appendix Table A1 for a complete list of outcomes). The first two columns of the table show the average beliefs for those outcomes where the survey elicited beliefs in both states of the world. The average treatment effects shown in column (3) are of particular interest. Since we can compute the individual-level treatment effects, columns (4)–(7) of the table show the cross-sectional heterogeneity in the treatment effects.

Subjective treatment effects.

Notes: Δ : change. Prop. Δ >0: proportion of students for whom the individual level Δ is positive. Prop. Δ =0: proportion of students for whom the individual level Δ is zero. 25th and 75th percentiles of the cross-sectional distribution of Δ . Standard deviation in parentheses. ( ∗  :  p <0.1, ∗∗  :  p <0.05, ∗∗∗  :  p <0.01).

We see that the average treatment effects are statistically and economically significant for all outcomes. The average impacts on academic outcomes, shown in Panel A, are mostly negative. For example, the average subjective treatment effect of COVID-19 on semester-level GPA is a decline of 0.17 points. More than 50% of the students in our sample expect a decrease in their GPA due to the treatment (versus only 7% expecting an increase). Additionally, 13% of the participants delayed their graduation, 11% withdrew from a class during the spring semester, and 12% stated that their major choice was impacted by COVID-19. 8

While almost no students report planning to drop out due to COVID-19, on average they expect to take a break from ASU in the fall 2020 semester at nearly twice the historical rate. Admittedly, the decision to take a break during a pandemic may be different than in more normal times. However, a substantial increase in the share of students failing to continue their studies is concerning, as historically 28% of students who fail to re-enroll for a fall semester do not return to ASU or another university within 5 years.

Regarding the impact of the pandemic on major choice, students who report that COVID-19 impacted their major choice were more likely to be in lower-paying majors before the pandemic; mean pre-COVID major-specific annual earnings were $43,053 ($46,943) for students whose major choice was (not) impacted by COVID-19. 9 Impacted students were also 9.3 percentage points less likely to be in a science, technology, engineering, or math (STEM) major before COVID-19. 10 We are only able to observe pre- and post-COVID major choices for the subset of students who had switched their major by the date of the survey. 11 Within this selected subsample of switchers, students chose to move into higher paying majors, with an average change in first-year earnings of $3,340. These patterns are generally consistent with the finding that students tend to gravitate towards higher-paying majors when exposed to adverse economic conditions when in college ( Blom et al., 2019 ).

An interesting and perhaps unanticipated result reported in Table 2 is that, on average, students are 4 percentage points less likely to opt for online instruction if given the choice between online and in-person instruction due to their experience with online instruction during the pandemic. 12 13 However, there is a substantial amount of variation in terms of the direction of the effect: 31% (47%) of the participants are now more (less) likely to enroll in online classes. We explore this heterogeneity in more detail in the next section, but it seems that prior experience with online classes somewhat ameliorates the negative experience; the average treatment effect for students with prior experience in online classes is a 2.4 percentage points decrease in their likelihood of enrolling in online classes, versus a 9.5 percentage points decline for their counterparts (difference statistically significant at the 0.1% level).

This large variation in the treatment effects of COVID-19 is apparent in several of the other outcomes, such as study hours, where the average treatment effect of COVID-19 on weekly study hours is −0.9 (that is, students spend 0.9 less hours studying per week due to COVID-19). The interquartile range of the across-subject treatment effect demonstrates substantial variation, with the pandemic decreasing study time by 5 hours at the 25th percentile and increasing study time by 4 hours at the 75th.

Overall, these results suggest that COVID-19 represents a substantial disruption to students' academic experiences, and is likely to have lasting impacts through changes in major/career and delayed graduation timelines. Students' negative experiences with online teaching, perhaps due to the abruptness of the transition, also has implications for the willingness of students to take online classes in the future.

Turning to Panel B in Table 2 , we see that students' current and expected labor market outcomes were substantially disrupted by COVID-19. As for the extensive margin of current employment, on average, 29% of the students lost the jobs they were working at prior to the pandemic (67% of the students were working prior to the pandemic), 13% of students had their internships or job offers rescinded, and 61% of the students reported that a close family member had lost their job or experienced an income reduction. The last statistic is in line with findings from other surveys of widespread economic disruption across the US. 14 Respondents experienced an average decrease of 11.5 hours of work per week and a 21% decrease in weekly earnings, although there was no change in weekly earnings for 52% of the sample, which again reflects substantial variation in the effects of COVID-19 across students.

In terms of labor market expectations, on average, students foresee a 13 percentage points decrease in the probability of finding a job by graduation, a reduction of 2% in their reservation wages, and a 2.3% decrease in their expected earnings at age 35.

The significant changes in reservation wages and expected earnings at age 35 demonstrate that students expect the treatment effects of COVID-19 to be long-lasting. Qualitatively, this is broadly consistent with the literature on graduating during recession. Oreopoulos et al. (2012) finds that graduating during a recession in which the unemployment rate increases 5% implies an initial loss in earnings of 9%, that decreases to 4.5% within 5 years and disappears after 10 years for a sample of male college graduates in Canada. Similarly, Schwandt and von Wachter (2019) find a 2.6% reduction in earnings 10 years after graduation for a 3-percentage point increase in unemployment at graduation, and Kahn (2010) finds an even longer-lasting effect on wages.

A large literature has investigated the impact of graduating during recessions on unemployment rates. Kahn (2010) finds that during the 1980's recession, the probability of being employed right after graduation for white males was largely unaffected by economic conditions. Altonji et al. (2016) only find what they term modest impacts. On the other hand, Rothstein (2020) finds that, for 22 to 23-year-olds graduating from college during the Great Recession, the probability of being employed decreases by 0.7 percentage point for every 1 percentage point increase in the unemployment rate. Using the estimates in Rothstein (2020) and the approximate 10 percentage point increase in the unemployment rate during April 2020, a back-of-the-envelope calculation indicates a 7 percentage point reduction in the probability of being employed for the graduating cohort in our sample. We find that students who are graduating in spring or summer 2020 expect a 35 percentage point decline in the likelihood of finding a job before graduation. While it is difficult to precisely map pre-graduation job finding rates to unemployment over the subsequent year, a 7 percentage point increase in unemployment appears low compared to the impact on students' expectations. It could be the case that the literature estimates are not appropriate for a situation as unexpected and different as a global pandemic, where the economic recession goes hand in hand with health concerns. Having said that, it could also be that students are overreacting to the COVID-19 shock. Data that tracks students' expectations and outcomes over time may be able to shed light on this.

4.2. Heterogeneous effects

We next explore demographic heterogeneity in the treatment effects of COVID-19. Fig. 1 plots the average treatment effects across several relevant demographic divisions including gender, race, parental education, and parental income. Honors college status and cohort are also included as interesting dimensions of heterogeneity in the COVID-19 context. The figure shows the impacts for six of the more economically meaningful outcomes from Table 2 (additional outcomes can be found in Appendix Fig. A2 ).

Treatment effects by demographic group.

(a) Delay Graduation due to COVID (0/1)

(b) Semester GPA ( Δ 0–4)

(c) Change major due to COVID (0/1)

(d) Likelihood take online classes ( Δ 0–1)

(e) Probability job before graduate ( Δ 0–1)

(f) Expected earnings at age 35 (Pct. Δ )

Notes: bars denote 90% confidence interval.

At least four patterns of note emerge from Fig. 1 . First, compared to their classmates, students from disadvantaged backgrounds (lower-income students defined as those with below-median parental income, racial minorities, and first-generation students) experienced larger negative impacts for the academic outcomes, as shown in the first three panels of the figure. 15 The trends are most striking for lower-income students, who are 55% more likely to delay graduation due to COVID-19 than their more affluent classmates (0.16 increase in the proportion of those expecting to delay graduation versus 0.10), expect 30% larger negative effects on their semester GPA due to COVID-19, and are 41% more likely to report that COVID-19 impacted their major choice (these differences are statistically significant at the 5% level). For some academic outcomes, COVID-19 had similarly disproportionate effects on nonwhite and first-generation students, with nonwhite students being 70% more likely to report changing their major preference compared to their white peers and first-generation students being 50% more likely to delay their graduation than students with college-educated parents. Thus, while on average COVID-19 negatively impacted several measures of academic achievement for all subgroups, the effects are significantly more pronounced for socioeconomic groups which were predisposed towards worse academic outcomes pre-COVID. 16 The pandemic's widening of existing achievement gaps can be seen directly in students' expected Semester GPA. Without COVID-19, lower-income students expected a 0.052 lower semester GPA than their higher-income peers. With COVID-19, this gap nearly doubles to 0.098. 17

Second, Panel (d) of Fig. 1 shows that the switch to online learning was substantially harder for some demographic groups; for example, men are 7 percentage points less likely to opt for an online version of a course as a result of COVID-19, while women do not have a statistically significant change in their online preferences. We also see that Honors students revise their preferences by more than 2.5 times the amount of non-Honors students. As we show later (in Table 4 ), these gaps persist after controlling for household income, major, and cohort, suggesting that the switch to online learning mid-semester may have been substantially more disruptive for males and Honors students. While the effect of COVID-19 on preferences for online learning looks similar for males and Honors students, our survey evidence indicates that different mechanisms underpin these shifts. Based on qualitative evidence, it appears that Honors students had a negative reaction to the transition to online learning because they felt less challenged, while males were more likely to struggle with the learning methods available through the online platform. 18 One speculative explanation for the gender difference is that consumption value of college amenities is higher for men (however, Jacob et al. (2018) , find little gender difference in willingness to pay for the amenities they consider).

Composition of COVID effects.

Notes: Standard errors in parentheses bootstrapped with 1000 replications. Each column reports results from a separate OLS regression of the dependent variable onto the covariates (row variables). Dependent variables measured in percentage points. ( ∗  :  p <0.1, ∗∗  :  p <0.05, ∗∗∗  :  p <0.01).

The third trend worth highlighting from Fig. 1 is that Honors students were better able to mitigate the negative effect of COVID-19 on their academic outcomes (panels a, b, and c), despite appearing to be more disrupted by the move to online learning (panel d). Honors students report being less than half as likely as non-Honors students to delay graduation and change their major due to COVID-19. Extrapolating from these patterns provides suggestive evidence that academic impacts for students attending elite schools– the group more comparable to these Honors students– are likely to have been small relative to the impacts for the average student at large public schools.

Finally, the last two panels of Fig. 1 present the COVID effect on two labor market expectations and show much less meaningful heterogeneity across demographic groups compared to the academic outcomes in previous panels. This suggests that, while students believe COVID-19 will impact both their academic outcomes and future labor market outcomes, they do not believe there is a strong connection between these domains. Supporting this observation, the individual-specific treatment effect on semester GPA is only weakly correlated with the individual-specific treatment effects on finding a job before graduation (corr = 0.0497, p  = 0.065) and expected earnings at 35 (corr = 0.0467, p  = 0.077).

The one notable exception to the lack of heterogeneity in panels (e) and (f) of Fig. 1 are seniors, who on average revised their subjective probability of finding a job before graduation three times as much as other cohorts. Appendix Fig. A3 further breaks down the estimated COVID-19 effects by expected year of graduation. Perhaps unsurprisingly, the 2020 cohort expects much larger effects on immediate job market outcomes such as reservation wages and probability of finding a job before graduation. While average expected changes to job market outcomes are noisier for academically younger students, perhaps reflecting additional uncertainty about the longer-term impacts of COVID-19, they appear to anticipate meaningful changes to their future labor market prospects. Conversely, younger students also expected larger disruptions to academic outcomes such as semester GPA and study time.

5. Understanding the heterogeneous effects

This section presents mediation analysis on the drivers of the underlying heterogeneity in the treatment effects. The COVID-19 pandemic serves as both an economic and a health shock. However, these shocks may have been quite heterogeneous across the various groups, and that could partly explain the heterogeneous treatment effects we documented in the previous section.

5.1. Economic and health mediating factors

We proxy for the financial and health shocks due to COVID-19 by relying on a small but relevant set of covariates which capture more fundamental or first-order disruptions from the pandemic. Financial shocks are characterized based on whether a student lost a job due to COVID-19, whether a student's family members lost income due to COVID-19, the change in a student's monthly earnings due to COVID-19, and the likelihood a student will fail to fully meet debt payments in the next 90 days. To measure health shocks, we consider a student's belief about the likelihood that they will be hospitalized if they contract COVID-19, a student's belief about the likelihood that they will have contracted COVID-19 by summer, and a student's subjective health assessment. Finally, in order to summarize the combined effect of each set of proxies, we construct principal component scores as one-dimensional measures of the financial and health shock to students. 19

Table 3 reports summary statistics of the different economic and health proxies by demographic group. Given the results in Fig. 1 , the remainder of the analysis will focus on three socioeconomic divisions: parental income, gender, and Honors college status. Our data indicate that lower-income students faced larger health and economic shocks as compared to their more affluent peers. In particular, they are almost 10 percentage points more likely to expect to default on their debt payments compared to their higher-income counterparts. Additionally, lower-income students are 16 percentage points more likely to have had a close family member experience an income reduction due to COVID-19. Regarding the health proxies, lower-income students rate their health as worse than higher-income students and perceive a higher probability of being hospitalized if they catch the virus. Finally, the differences in economic and health shocks between lower and higher-income students, as summarized by the principle components of the selected proxy variables, are statistically significant.

Summary statistics for economic and health proxies.

Notes: P-value columns report the p-value of a difference in means test between the two columns indicated by the numbers in the heading.

Columns (5)–(7) of Table 3 show that both economic and health shocks are larger for non-Honors students. In fact, the average differences in the principal component scores for both the economic and health factors is larger for these two groups than for the income groups. Likewise, the last three columns of the table show that women experienced larger COVID-19 shocks due to economic and health factors. These differences are partly driven by the fact that, in our sample, females are more likely to report that they belong to a lower-income household than males (50% vs. 42%).

In short, Table 3 makes clear that the impacts of COVID-19 on the economic well-being and health of students have been quite heterogeneous, with lower-income and lower-ability students being more adversely affected.

5.2. The role of economic and health shocks on explaining the COVID-19 effects

To investigate the role of economic and health shocks in explaining the heterogeneous treatment effects (in Section 4.2 ), we estimate the following specification:

where Δ i is the COVID-19 treatment effect for outcome O on student i . Demog i is a vector including indicators for gender, lower-income, Honors status, and dummies for cohort year and major. FinShock i and HealthShock i are vectors containing the shock proxies or their principal component. Finally, ε i denotes an idiosyncratic shock.

The parameters of interest are α 2 and α 3 . A causal interpretation of these parameters requires FinShock i and HealthShock i to be independent of ε i . This seems unlikely in our context as unobservables correlated with FinShock i and HealthShock i may also modulate COVID-19's impact on academic outcomes. Therefore, we prefer to interpret α 2 and α 3 as simple correlations. Nevertheless, we believe this descriptive evidence can be informative from a policy perspective.

Table 4 shows estimates of Eq. (2) for four different outcomes ( Appendix Table A2 shows the estimates for additional outcomes). For each outcome, five specifications are reported ranging from controlling for only demographic variables in the first specification to controlling for both economic and health factors in the fourth specification. Finally, the last column includes only the principal component of each shock to provide insight about overall effects, given that certain shock proxies show high levels of correlation (see Appendix Table A4 for the correlations within each set of proxies).

Several important messages emerge from Table 4 . First, both shocks are (economically and statistically) significant correlates of the COVID-19 effects on students' outcomes. In particular, F-tests show that the financial and health shock proxies are jointly significant across almost all specifications. 20 This is also reflected in the statistical significance of the principal components. Moreover, the fact that the effect of key proxy variables remains robust when we simultaneously control for both shocks demonstrates the robustness of our results. For example, we find that a 50 percentage point increase in the probability of being late on debt payments is associated with an increase in the probability of delaying graduation and switching majors due to COVID-19 of 6.9 and 6.4 percentage points respectively. These effects are large given that they represent more than half of the overall COVID-19 treatment effect for these variables. Similarly, we find that an analogous increase in the probability of hospitalization if contracting COVID-19 is associated with a 6 and 5 percentage points increase in the probability of delaying graduation and switching majors due to COVID-19.

Second, in terms of labor market expectations, we find that the change in the expected probability of finding a job before graduation strongly depends on having a family member that lost income (which is also correlated with the student himself losing a job). In particular, the size of this effect represents 32% of the overall COVID-19 treatment effect. Therefore, this finding suggests that students' labor market expectations are driven in large part by personal/family experiences.

Third, although the proxies play an important role in explaining the pandemic's impact on students, there is still a substantial amount of variation in COVID-19 treatment effects left unexplained. Across the four outcomes in Table 4 , the full set of proxies explain less than a quarter of the variation in outcomes across individuals. Appendix Fig. A4 visualizes this variation by plotting the distribution of several continuous outcomes with and without controls. While the interquartile range noticeably shrinks after conditioning on the proxy variables, these plots highlight the large amount of variation in treatment effects remaining after conditioning on the proxies.

Finally, our results show that the financial and health shocks play an important role in explaining the heterogeneous effects of the COVID-19 outbreak. In particular, columns (4) and (9) demonstrate that economic and health factors together can explain approximately 40% and 70% of the income gap in COVID-19's effect on delayed graduation and changing major respectively. The gap between Honors and non-Honors students is likewise reduced by 27% and 39% for the same outcomes. Taken together, these results imply that differences in the magnitude of COVID-19's economic and health impact can explain a significant proportion of the demographic gaps in COVID-19's effect on the decision to delay graduation, the decision to change major, and preferences for online learning. These results are important and suggest that focusing on the needs of students who experienced larger financial or health shocks from COVID-19 may be an effective way to minimize the disparate disruptive effects and prevent COVID-19 from exacerbating existing achievement gaps in higher education.

6. Conclusions

This paper provides the first systematic analysis of the effects of COVID-19 on higher education. To study these effects, we surveyed 1500 students at Arizona State University, and present quantitative evidence showing the negative effects of the pandemic on students' outcomes and expectations. For example, we find that 13% of students have delayed graduation due to COVID-19. Expanding upon these results, we show that the effects of the pandemic are highly heterogeneous, with lower-income students 55% more likely to delay graduation compared to their higher-income counterparts. We further show that the negative economic and health impacts of COVID-19 have been significantly more pronounced for less advantaged groups, and that these differences can partially explain the underlying heterogeneity that we document. Our results suggest that by focusing on addressing the economic and health burden imposed by COVID-19, as measured by a relatively narrow set of mitigating factors, policy makers may be able to prevent COVID-19 from widening existing achievement gaps in higher education.

Declaration of competing interest

The authors declare that they have no relevant or material financial interests that relate to the research described in this paper. There are no declarations of interest.

☆ Noah Deitrick and Adam Streff provided excellent research assistance. All errors that remain are ours.

1 See, the New York Times article “ After Coronavirus , Colleges Worry : Will Students Come Back ?” (April 15, 2020) for a discussion surrounding students' demands for tuition cuts.

2 In some cases, instead of asking students for the outcomes in both states of the world, we directly ask for the difference. For example, the survey asked how the pandemic had affected the student's graduation date.

3 This approach has been used successfully in several other settings, such as to construct career and family returns to college majors ( Arcidiacono et al., 2020 ; Wiswall and Zafar, 2020 ), and the causal impact of health on retirement ( Shapiro and Giustinelli, 2019 ).

4 The income gap in GPA increased from 0.052 to 0.098 on a 4 point scale. It is significant at the 1% level in both scenarios.

5 The 64 people taking the survey at the moment the target sample size (1500) was reached were allowed to finish.

6 59% of Honors students in our sample report living on campus.

7 This is different from asking students in normal times about their expected outcomes in a state with online teaching and no campus activities (COVID-19) since most students would not have had any experience with this counterfactual prior to March this year.

8 Altonji et al. (2016) finds a small but positive effect on the probability of attending graduate school when graduating into a recession. This is suggestive evidence that students try to avoid entering the labor market when economic conditions are adverse. Our results on delayed graduation are consistent with students avoiding entering the labor market at inopportune times.

9 For this calculation, we take earnings data from the US Department of Education College Scorecard dataset. Major-specific earnings are calculated using median first-year earnings for ASU graduates in 2015 and 2016 by two-digit CIP code. Observable earnings averaged within major category.

10 STEM major designation made using two-digit CIP code and The STEM Designated Degree Program from the US Department of Homeland Security.

11 This includes 77 respondents, or 43% of those who say COVID-19 impacted their major choice.

12 The relevant survey question read: “ Suppose you are given the choice to take a course online/remote or in-person . [ Had you NOT had experience with online/remote classes this semester ], what is the percent chance that you would opt for the online/remote option ?”

13 This result is in line with a survey about eLearning experiences across different universities in Washington and New York that concludes that 75% of the students are unhappy with the quality of their classes after moving to online learning due to COVID-19.

14 According to the US Census Bureau Household Pulse Survey Week 3, 48% of the surveyed households have experienced a loss in employment income since March 13 2020.

15 The cutoff for median parental income in our sample is $80,000.

16 Based on analysis of ASU administrative data including transcripts, we find that, relative to their counterparts, first-generation, lower-income, and non-white students drop out at higher rates, take longer to graduate, have lower GPAs at graduation, and are more likely to switch majors when in college (see Appendix Table A3 ).

17 The difference is significant at 1% in both cases.

18 Honors students were as likely as non-Honors students to say that classes got easier after they went online but, conditional on saying classes got easier, were 47% more likely to say “homework/test questions got easier.” Conversely, males were marginally more likely to say classes got harder after they went online (10% more likely, p  = 0.055) and, conditional on this, were 14% more likely to say that “online material is not clear”.

19 Eigenvalues indicate the presence of only one principal component for each of the shocks.

20 The only exception is the financial shock when explaining changes in the probability of taking classes online.

Expected and previous academic performance.

Notes: Figure plots mean expected GPA with COVID-19 against students' cumulative GPA up to the spring 2020 semester. The 45 degree line is also plotted for reference.

More treatment effects by demographic group.

(a) Withdrew from Class due to COVID (0/1); (b) Social Events per Week ( Δ 0–14); (c) Move in With Family due to COVID (0/1); (d) Weekly Study Hours ( Δ 0–40); (e) Reservation Wage (Pct. Δ )

Notes: Bars denote 90% confidence interval.

Cohort trends.

Notes: Figure plots average COVID-19 effects for a series of outcomes. The x-axis variable in each panel is expected academic year of graduation (after COVID), with summer graduation dates included in the previous academic year. Bars denote 90% confidence interval.

Distribution of individual effects.

Notes: Data winsorized below 5% and above 95%. Controls include cohort fixed effects, major fixed effects, and the economic/health proxies in Table 3 . Conditional distribution adjusted to preserve unconditional mean. Within each plot: middle line represents median, edges of box represent interquatile range (IQR), edge of whisker represents the adjacent values or the 25th(75th) percentile plus(minus) 1.5 times the IQR. Outlier observations past adjacent values plotted as individual points.

Composition of COVID effects: more outcomes.

Notes: Standard errors in parentheses bootstrapped with 1000 replications. Each column reports results from a separate OLS regression of the dependent variable onto the covariates (row variables). Dependent variables measured in percentage points (except GPA). ( ∗  :  p <0.1, ∗∗  :  p <0.05, ∗∗∗  :  p <0.01).

Existing achievement gaps.

Notes: Sample includes all first time freshman at ASU's main campus who started within the last 10 years. N  = 58,426. ( ∗  :  p <0.1, ∗∗  :  p <0.05, ∗∗∗  :  p <0.01).

Correlation of shock proxies.

Notes: Table reports correlation matrix for indicated variables.

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Report | Coronavirus

COVID-19 and student performance, equity, and U.S. education policy : Lessons from pre-pandemic research to inform relief, recovery, and rebuilding

Report • By Emma García and Elaine Weiss • September 10, 2020

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Pandemic-relevant research offers key lessons as the education system responds to the coronavirus crisis:

• Research regarding online learning and teaching shows that they are effective only if students have consistent access to the internet and computers and if teachers have received targeted training and supports for online instruction. Because these needed requirements for effectiveness have been largely absent for many, remote education during the pandemic has impeded teaching and learning.
• Research on home schooling shows that it works well for students for whom intentional, personalized, and sufficient resources are available. The crisis-induced delivery of home schooling without time for planning around children’s learning styles and circumstances means that many children home schooled during the pandemic are not replicating such model and thus not reaping the associated benefits.
• Reduced learning time has likely impeded student learning and also affected the development of the whole child. Once the pandemic allows it, we will need to make up for this time by increasing both the amount and quality of learning time—through extended schedules, summer enrichment and after-school activities, more personalized instruction, and staffing strategies that reduce class sizes and staff schools with sufficient and highly credentialed educators.
• Research on chronic absenteeism and on remote learning reinforces the urgency of providing appropriate support to children who are least prepared and especially to those at risk of becoming disengaged and eventually dropping out.
• Research on summer learning (loss or gain) points to the importance of personalized instruction. The research shows that learning styles and outcomes vary greatly, and that the outcomes are a function of the educational resources that families and systems provide to children across the year and of a large number of factors and circumstances that shape children’s learning and development.
• Research shows that a lack of contingency planning exacerbates the negative impacts of recessions, natural disasters, and pandemics on learning. Contingency planning thus needs to be institutionalized and include emergency funding to replenish the resources drained during emergencies.

What we know about the pandemic’s consequences for education so far helps us plan next steps:

• Learning and development have been interrupted and disrupted for millions of students. The only effective response is to use diagnostic tests and other tools to meet each child where he or she is and to devise a plan for making up for the interruptions.
• The pandemic has exacerbated well-documented opportunity gaps that put low-income students at a disadvantage relative to their better-off peers. Opportunity gaps are gaps in access to the conditions and resources that enhance learning and development, and include access to food and nutrition, housing, health insurance and care, and financial relief measures.
• One of the most critical opportunity gaps is the uneven access to the devices and internet access critical to learning online. This digital divide has made it virtually impossible for some students to learn during the pandemic.
• The pandemic has exacerbated the limitations of standardized tests, which reward a narrow set of skills and more affluent students who have access to specialized instruction. Such tests could overwhelm or label children when what they need now are diagnostic assessments and needs-based assessments that assess where they are across a range of domains and what they need going forward.

Informed by our learning, here is a three-pronged plan for addressing the adverse impacts of COVID-19 on education and rebuilding stronger:

• Relief: Give schools urgent resources so that they can provide effective remote instruction and supports at scale during the pandemic.
• Recovery: Provide extra investments to help students and schools make up lost ground as they return to in-school operations.
• Rebuilding: Redesign the system to focus on nurturing the whole child, balancing cognitive with socioemotional skills development and ensuring that all children have access to the conditions and resources that enhance learning and development.

Introduction

The COVID-19 pandemic is overwhelming the functioning and outcomes of education systems—some of which were already stressed in many respects. This is true across the world and affects all children, though to differing degrees depending on multiple factors—including the country/region where they live, as well as their ages, family backgrounds, and degree of access to some “substitute” educational opportunities during the pandemic. In early spring as the pandemic was hitting its first peak, the virus consigned nearly all of over 55 million U.S. school children under the age of 18 to staying in their homes, with 1.4 billion out of school or child care across the globe (NCES 2019a; U.S. Census Bureau 2019; Cluver et al. 2020). Not only did these children lack daily access to school and the basic supports schools provide for many students, but they also lost out on group activities, team sports, and recreational options such as pools and playgrounds.

( COVID-19 & Education Webinar : Join us Wednesday for a discussion on this report, including opening remarks from Randi Weingarten, the president of the 1.7 million-member American Federation of Teachers, AFL-CIO, about the state of COVID-19 and education and what needs to be done now to support educators and mitigate the damage to student performance, especially the most vulnerable children. Register here. )

The shutdown of schools, compounded by the associated public health and economic crises, poses major challenges to our students and their teachers. Our public education system was not built, nor prepared, to cope with a situation like this—we lack the structures to sustain effective teaching and learning during the shutdown and to provide the safety net supports that many children receive in school. While we do not know the exact impacts, we do know that children’s academic performance is deteriorating during the pandemic, along with their progress on other developmental skills. We also know that, given the various ways in which the crisis has widened existing socioeconomic disparities and how these disparities affect learning and educational outcomes, educational inequities are growing (Rothstein 2004; Putnam 2015; Reardon 2011; García and Weiss 2017). As a consequence, many of the children who struggle the hardest to learn effectively and thrive in school under normal circumstances are now finding it difficult, even impossible in some cases, to receive effective instruction, and they are experiencing interruptions in their learning that will need to be made up for.

The 2020–2021 school year is now underway, and with many schools remaining physically closed as the 2020–2021 year begins, there is more we need to understand and think through if we are to meet the crisis head-on. If students are to not see their temporary interruptions become sustained and are to regain lost ground, if teachers are to do their jobs effectively during and after the pandemic, and if our education system is to deliver on its excellence and equity goals during the next phases of this pandemic, it will be critical to identify which students are struggling most and how much learning and development they have lost out on, which factors are impeding their learning, what problems are preventing teachers from teaching these children, and, very critically, which investments must be made to address these challenges. For each child, this diagnostic assessment will deliver a unique answer, and the system will have to meet the child where he or she is. A strengthened system based on meeting children where they are and providing them with what they need will be key to lifting up children.

This report briefly reviews the relevant literature on educational settings that have features in common with how education is occurring during the crisis and emerging evidence on opportunity gaps during the COVID-19 pandemic in order to propose a three-pronged plan. The plan covers the three Rs: (immediate) relief for schools, (short-term) recovery, and (long-term) rebuilding for schools and the education system as a whole.

Children are not in their schools: What should we expect the consequences to be?

The current downturn is unique, and in most ways it is much more severe than any we have experienced in recent history. Almost overnight, the pandemic forced the cancellation of the traditional learning that takes place in school settings. It imposed substantial alterations in the “inputs” used to produce education—typically all the individual, family, teacher, school, etc., characteristics or determinants that affect “outcomes” like test scores and graduation rates. The pandemic has affected inputs at home too, as families and communities juggling health and work crises are less able to provide supports for learning at home. 1 Because there are no direct comparisons to past events or trends, we are without fully valid references for assessing the likely impacts of the COVID-19 crisis on children. There are, however, specific aspects of this crisis that have arisen in other contexts and been studied by education researchers, and we can derive from them some guidance on topics such as the loss of learning time and use of alternative learning modes.

Here we thus summarize research findings on aspects of education that appear most pertinent to the current crisis. We selected this set of studied conditions because they represent situations in which children are out of school in large numbers or using the unusual learning tools that have become typical in recent months. As discussed in the sections below, however, the sudden, severe, and universal nature of this crisis means that the current contexts in which students are currently “absent,” engaged in “remote learning,” or “homeschooled” are very different during the pandemic. However, while these findings are only partially applicable to the situations arising during this pandemic, if we dig into why various modes of learning worked or did not work well, it can help guide how to improve learning as education continues under the pandemic—and how to lift children up once schools recover their normal mode of operation. 2

Decreased learning time has likely impeded student learning

The school lockdowns that started in the spring of 2020 reduced instructional and learning time, which are known to impede student performance, with disparate impacts on different groups of students.

Research on time in school anticipates the consequences of having learning interrupted

International and U.S. data provide a benchmark of what can be considered usual educational progress over a given school year. Here we look at data on reading, math, and science test results of 15-year-old students in countries all over the world from the Programme for International Student Assessment (PISA) run by the Organisation for Economic Co-operation and Development (OECD 2009) and data on a cohort of U.S. children who entered kindergarten in 2010 for the 2010–2011 school year from Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (ECLS-K-2010–2011), run by the U.S. Department of Education, National Center for Education Statistics (NCES 2010–2011). From these studies, it has been estimated how much children learn over a school year (to make the estimates of how far the group’s average score on skills were at the end of the year from their skill levels at the beginning of a year comparable across studies, we use standard deviations). On average, students advance in their academic performance by between about 0.3 standard deviations (SD) and 0.5 SD to 0.7 SD per year, depending on their age and subject/skill (OECD 2009; own analysis based on NCES 2010–2011). 3 The 2019–2020 school year was cut by at least one third relative to its normal length, which, assuming linear increments in growth over the year and no major other obstacles, suggests a loss of at least 0.1 SD across the board, and larger in earlier grades. These benchmarks will be helpful as we look at the various ways that students have seen their learning interrupted and disrupted this year, and they will continue to do so in 2020–2021.

It is useful as well to examine the research on the length of the school day, which has identified a causal relationship between the amount of (high-quality) instructional time and student performance (Figlio, Holden, and Özek 2018; Goodman 2014; Kidronl and Lindsay 2014; Jin Jez and Wassmer 2013; Marcotte and Hansen 2010). Challenges, though, arise in most evaluations because it is difficult to disentangle the effects of the length of the school day from the effects of starting the school day earlier, or switching to a four-day school week, or to year-round instruction. 4

Figlio, Holden, and Özek (2018) find that extending the school day by an hour to provide literacy instruction increases reading scores by 0.05 SD in elementary schools. Thompson (2019) explains that school days lost due to weather-related cancellations negatively impact performance (citing Marcotte 2007; Marcotte and Hemelt 2008), and that the positive impact of a four-day school week on performance is due to the longer school day, the increased flexibility, and the expanded total learning time over the year. He finds a negative effect (0.03–0.05 SD) of four-day school weeks on performance in Oregon, where weekly instructional time was lower in the districts adopting this model.

Research on summer learning losses and gains show that these vary widely

Another body of research that speaks to potential lost learning time arises from studies of so-called summer learning loss. In earlier research, researchers consistently found that test scores for low-income students would decrease over the summer, while test scores for better-off students would stay constant or increase slightly (Kuhfeld 2019 based on Cooper et al. 1996). 5 (This pattern has also been referred to in some studies as “slide” or “setback”). A limitation of this earlier research, however, was that the samples represented students who were in school in the 1970s and 1980s—and thus were exposed to very different circumstances than their current counterparts. 6

The findings from more recent evidence on summer learning are less consistent. One study reveals a substantial learning loss over the summer of about one to two months in reading and from one to three months of school-year learning in math (Kufheld 2019). Others find that, on average, the change in scores over the summer is near zero—which von Hippel, Workman, and Downey (2018) have renamed “summer slowdown” or “summer stagnation.” Researchers tend to agree, though, on the fact that there is a large variation in summer learning among students, and on the fact that gaps between students of differing socioeconomic status (SES)—specifically high- and low-SES students—widen (Atteberry and McEachin 2020; Kuhfeld 2019; von Hippel, Workman, and Downey 2018). 7

Multiple factors are used to explain the variation in these findings. In addition to differences in the educational resources that families provide children across the year, there are a large number of factors that appear to affect learning and are of particular relevance in the current context when trying to gauge the level of learning that has taken place during the pandemic: these findings on summer learning (loss or gain) reflect the great range of learning styles that students exhibit during the summer, or when schools are not in session, i.e., learning styles and outcome levels vary greatly because students have different innate individual characteristics and their learning and development is shaped by multiple factors and circumstances, in and out of school. This fact will be critically important when schools are back in session in the following two ways. First, when educators measure and assess children’s learning, they will need to consider that there are many ways that children learn and many types of knowledge that they acquire beyond math and reading. In other words, teaching and assessing children needs to be done within a framework that understands that each child may have learned differently and may have learned different things. Second, when designing how to best lift children up to make up for the extended out-of-school sessions and disruptions, it will be critical to create more personalized instruction and extend learning (see the policy section at the end of the report).

Research on chronic absenteeism reinforces the urgency of tending children at risk of becoming disengaged

The literature on student absenteeism also sheds light on the relationship between learning and instructional time. The evidence indicates that the negative relationship between absenteeism and student outcomes becomes more intense the more school days that a student misses. Using data from public schools in Chicago, Allensworth and Evans (2016) noted that each week of absence per semester in ninth grade is associated with a more than 20% decline in the probability of graduating from high school. With respect to performance, the disadvantage associated with absenteeism grows as the number of days missed increases: students who missed 1–2 school days, 3–4 days, 5–10 days, or more than 10 days scored, respectively, 0.10, 0.29, 0.39, and 0.64 SD below students who missed no school on mathematics performance for eighth graders (García and Weiss 2018; see Figure A reproduced below).

As this correlation between days absent and declining test scores indicates, there also seems to be a point after which the disadvantage becomes much larger. Indeed, researchers put a strong emphasis on “chronic absenteeism” as the critical indicator, as students who are chronically absent are at serious risk of falling behind in school, having lower grades and test scores, exhibiting behavioral issues, and, ultimately, dropping out (Balfanz 2017; U.S. Department of Education 2016; Gottfried and Ehrlich 2018). 8 Indeed, the risk of dropping out is of particular concern for students for whom the pandemic may act as the revolving door but one that ushers them away from the school period (IES 2020; Dorn et al. 2020; Stancati, Brody, and Fontdeglòria 2020; Torres 2020). The United Nations has recently defined this as a “generational catastrophe” (United Nations 2020).

A final point to highlight from this body of research is the range of reasons for, and thus strategies needed to reduce, student absenteeism. There are multiple reasons why students miss classes, as well as large differences in the absenteeism rate among both individual students and student subgroups. Those seeking to develop effective policies to reduce absenteeism, especially chronic absenteeism, understand the need to examine the root causes—academic disengagement, socioemotional distress, economic challenges, health problems, and others. Initiatives that have been rigorously evaluated show that it is critical both to identify the specific reason(s) why a student is missing school and to respond with targeted, relevant supports. 9 This point is particularly relevant in the current context, in which so many students are frequently absent for a variety of reasons that may be difficult for teachers and schools to know or address.

The more frequently students miss school, the worse their performance : Performance disadvantage experienced by eighth graders who missed school relative to students with perfect attendance in the last month, by number of days missed (standard deviations)

The data below can be saved or copied directly into Excel.

The data underlying the figure.

Notes: Data reflect performance in the 2015 NAEP mathematics assessment. Estimates are obtained after controlling for race/ethnicity, poverty status, gender, IEP status, and ELL status; for the racial/ethnic composition of the student’s school; and for the share of students in the school who are eligible for FRPL (a proxy for school socioeconomic composition). All estimates are statistically significant at p < 0.01.

Source:  EPI analysis of National Assessment of Educational Progress microdata, 2015. Chart adapted from Figure A in García and Weiss 2018.

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Of course, the various approaches examined by the research on learning time assume two groups of students: those who are missing some learning time in school and those who are not. (In general, they compare “treatment” versus “nontreatment” groups to estimate impacts.) This comparison does not hold during the lockdown. Instead, all students are missing out on in-class instruction, and instead have been attending school remotely via various online arrangements that in some ways resemble homeschooling or online education. As discussed below, the evidence about homeschooling and remote education presents serious limitations, given their very different context, but nonetheless uncovers many issues that we will need to address in post-pandemic education.

Lacking the needed requirements for effectiveness, remote and alternative learning and online instruction during the pandemic has likely affected teaching and learning

The two main tools for education available to children during the lockdowns have been remote and alternative learning and, at least technically, a homeschooling environment. Evidence on these two modes make clear the conditions that would be needed in order for children to effectively learn under these conditions and for teachers to effectively teach under these conditions. As the following subsections show, most of these conditions have been lacking in recent months.

Research on effective online learning indicates it is critical that students have the tools and the experience

Online learning means, first and fundamentally, the shift from face-to-face learning to the use of devices of various sorts to deliver that learning. Successful online learning thus requires that students (and teachers) be familiar and proficient in their uses of those devices for learning. Of course, even more fundamentally, it requires that the devices exist. Here we discuss the needs of students.

We have limited knowledge about how much and for which purposes students have used devices and technology at home up to this point. An estimated 1.5 million K–12 students participated in some online learning in 2010 (Bettinger and Loeb 2017, based on Wicks 2010). 10 Figure B uses PISA data from 2018 for the United States to show that, while students spent extensive time online prior to the pandemic, that time was heavily spent on social activities, browsing or seeking information, playing games, or accessing email. Students spent less time on educational activities, such as school work or communicating with other students or teachers. These findings suggest that over the past few months as children transitioned suddenly to online learning, they did so without necessarily having the practice or experience to learn well online, and that the transition required them to shift their device-use habits from leisure to studying. What we also know is that remote learning demands that children ignore the distractions that are now in front of their faces all the time and to which they, like all of us, are naturally drawn. 11

What activities do 15-year-olds use digital devices for out of school and how often do they use them? : Frequency with which 15-year-olds use digital devices out of school for different activities, 2018

Note: Shares are based on the average use of digital devices out of school for selected activities under each type of activity.

Note: Shares are based on the average use of digital devices out of school for selected activities under each type of activity. “Social networks” includes the use of digital devices out of school for chatting online and for social networks (for example, Facebook); “Surfing” includes browsing the internet for fun videos (e.g., YouTube) and for downloading music, films, games or software from the Internet; “Emailing” includes using email; “Seeking information” includes reading news on the internet and obtaining practical information from the internet; “Games” includes playing one-player games and playing collaborative online games; “School work” references browsing the internet for school work (e.g., for preparing an essay or presentation, following up on lessons, downloading or uploading or browsing material from a school's website, and doing homework on a computer; and “Group communication” includes the use of digital devices out of school for  communication with other students about school work or for communication with teachers and submission of assignments.

Source : EPI analysis using Program for International Student Assessment (PISA) data for the U.S. (OECD 2018).

In addition to assessing quality and time, the literature on the use of devices assumes that all students have access to appropriate digital devices—i.e., it assumes no digital divide. As has been extensively documented, however, that is not the case. For example, García, Weiss, and Engdahl (2020) show that nearly 16% of eighth graders, or one in six who participated in the National Center for Education Statistics’ National Assessment of Educational Progress (NAEP) for 2017, do not have a desktop or laptop computer at home on which to follow their classes. And a small fraction of eighth graders, 4.2%, lack home internet, the other essential instrument for remote study. (It’s important to note that the survey questions do not ask about the quality or coverage of the internet access, or the number of computers in the house, and that the information predates the pandemic’s arrival. Devices once available for homework may now be shared with siblings or be used by parents for work. 12 )

A final caveat is that there is still limited evidence on the effectiveness of online education. A critical aspect highlighted by Bettinger and Loeb (2017) is that online courses are difficult, especially for the students who are least prepared. 13 Research on performance of children attending virtual charter schools confirms the importance of self-engagement and parental supervision for success with this mode of education. Also, selection into these schools (students disengaged with  traditional schools enter these schools); worse inputs (teacher-to-student ratios, one-on-one instruction, etc.) than in traditional schools; and other features of these schools translated into negative effects on performance. 14 Later in the report we discuss the requirements for successful online education from the perspective of teachers.

Research on home schooling makes clear that it works well for students under narrow circumstances

According to the NCES, close to 1.7 million students, or about 3.3% of K–12 students, were home-schooled in 2016 (NCES 2018). 15 Parents who home-schooled their children cited the following as the most important reasons for doing so: concerns about the school environment, such as safety, drugs, or negative peer pressure; dissatisfaction with academic instruction at available schools; and a desire to provide religious instruction (Grady 2017).

In terms of its effectiveness, performance of home-schooled students is generally higher than that of their non-home-schooled peers. A review of 14 studies found consistent positive results in 11, mixed results in another study (some positive and some negative results), zero impact in another study, and neutral and negative effects in a final one. The estimate of the effects (based on eight of the 14 studies for which this information was available) ranged from very small (0.05 SD) to extremely large (1.13 SD) (Ray 2017a). Using percentile metrics, home-schooled students scored, on average, at or above the 84th percentile in all subject areas (Ray 2017b). 16

While these findings may look promising, however, it is important to keep in mind two key considerations when interpreting these results. First, many more resources are devoted to home-schooled children, so they would be expected to perform higher, all else equal. Also, higher performance among home-schooled students may be due more to their selection into the category than the “treatment”/type of education they receive. 17

Belfield (2004), for example, suggests that the improved outcomes among students who are home-schooled could be due to flexible instruction (without age-tracking), small “class sizes,” and dedicated parent-teachers who should make home schooling more effective than other forms of education. He also notes that “educational outcomes may be skewed toward those on which the family has competence, and educational progress may be slow if there is no formative assessment or peer-pressure to learn (although home-school parents may exert more pressure or have higher expectations as a result of their supervision).” More recent studies suggest that parameters such as structured or unstructured instruction may also be important drivers of the results (Neuman and Guterman 2016).

These underlying factors could be particularly relevant in the current crisis. Many of the same stark distinctions between effective and ineffective online education and home schooling would apply to the “ emergency remote learning” done at home under a pandemic: students who entered the pandemic better off and those whose parents have been trained in instruction or have a particular ability teach would likely perform better than students whose parents have not been able to develop (or as successful at developing) those skills. In general, parents who were suddenly thrust into the role of home-schoolers had no such preparation; most are taking on that new task while juggling the full range of other home-care responsibilities as well as, in many cases, full-time remote jobs. That said, students whose parents have more formal education likely also have an advantage in this context—as they do in nonpandemic contexts—further compounding the disparities that low-income students are accruing (see, for example, Dinarski 2020; Rothstein 2020; Belfield 2004; Goldstein 2020a). 18

Evidence on online instruction emphasizes that teachers also need training and supports

As the discussion of successful versus unsuccessful remote and online learning reveals, there are multiple requirements needed for online education to work as intended and deliver positive results. Just as the requirements for effective student learning have largely not been met during the pandemic, the same is true for effective online instruction.

First, there was little time to design and develop instructional tools for wide deployment. 19 As a recent analysis of research on the subject details,

Online education, including online teaching and learning, has been studied for decades. Numerous research studies, theories, models, standards, and evaluation criteria focus on quality online learning, online teaching, and online course design. What we know from research is that effective online learning results from careful instructional design and planning, using a systematic model for design and development. The design process and the careful consideration of different design decisions have an impact on the quality of the instruction. And it is this careful design process that will be absent in most cases in these emergency shifts. 20 (Hodges et al. 2020)

Moreover, it is hard to plan and to design effective instruction for the COVID-19 era when teachers and school districts don’t have a framework (or even the right language) to accommodate what they are doing. As Hodges et al. (2020) emphasized when exploring how colleges and universities were coping with the sudden and rapid shift to remote learning (in March 2020), understanding the current circumstances required distinguishing between online or remote learning generally. For our current context, they suggested the term “emergency remote teaching,” which helps signal the uncertainties and unknowns that could affect teachers’ instruction.

Second, weak systems of support, including lack of professional development on how to integrate computers into instruction, have left teachers less than optimally equipped to teach during the pandemic. 21

Slightly over two in three public school teachers report having participated in professional development activities on the use of computers for instruction in the past 12 months, as shown in Figure C , based on García and Weiss 2019 using data from the 2011–2012 Schools and Staffing Survey (SASS). 22 But those who participated in these activities were not broadly satisfied with them. Among these teachers, one in four found the activity very useful, with about one in three finding it either not useful or just somewhat useful. And teachers who participate in such activities have to surmount barriers to do so, as access to work time and supports to participate in professional development are very limited. Among all teachers, only half have released time from teaching to participate in professional development (50.9 percent), and less than a third are reimbursed for conferences or workshop fees (28.2 percent). 23

Few teachers are well-trained in using computers for instruction

Shares of teachers who said they had training in the past 12 months on the use of computers for instruction, shares of teachers reporting usefulness of training they received in using computers for instruction.

Notes: Data are for teachers in public noncharter schools. The bottom figure shows shares of teachers who answered “very useful,” “useful,” “somewhat useful,” or “not useful” when asked, for the specific professional development activity, “Overall, how useful were these activities to you?”

Source : 2011–2012 Schools and Staffing Survey (SASS) microdata from the U.S. Department of Education’s National Center for Education Statistics (NCES). Adapted from García and Weiss 2019.

The limited training pre-pandemic is compounded by the limited technical support during the pandemic. Most K–12 teachers did not contemplate online instruction until being forced to do so by the pandemic. As a result, teachers have had to come up with a variety of options on the fly, from assigning daily or weekly coursework that students turn in online to full classes conducted via Zoom and a range of approaches in between. We can expect that some of these online strategies launched during the COVID-19 crisis did not lead to optimal outcomes.

Third, inadequate systems for tracking attendance online leave teachers in the dark on a key “input” of education: student learning time. Even the most well-trained teacher when it comes to online instruction won’t be effective if his or her students are not online and following instruction. At the most basic level, schools are trying to assess how broadly and consistently students are interacting with teachers and receiving instruction. One ambitious effort has been in Southern Florida, where districts rigorously track attendance and contact parents when students are absent. Quickly recognizing that relying on student log-ins failed to capture much of the activity taking place, districts in Palm Beach County and the Florida Keys ask teachers to log student participation in online forums and completion of assigned work. In general, schools in this system are seeing attendance that is only modestly lower than normal, with the biggest drop-offs among the youngest and oldest students (who, respectively, need parents’ help to get online and are least motivated to take part). However, while the system helps monitor potential race- and class-based disparities in attendance, concerns remain (Bakeman 2020). Attesting the importance of attendance, some school districts that have chosen online instruction for the beginning of the 2020–2021 school year are making registering attendance compulsory through their platforms. 24

Fourth, the emotional bonds critical to any kind of learning are just as important for remote learning or home schooling but hard to attain in the current crisis. Even more so than college professors, K–12 teachers also need to retain emotional bonds with their students, especially younger ones, that can be extremely difficult to attain remotely. Many of these teachers are also parents and so must juggle their children’s activities, such as helping their children with homework, with their own job responsibilities. And teachers working with particularly vulnerable students face additional challenges as some of these students lack access to computers to work or even enough internet bandwidth (see barriers to access described below).

The “whole-child” development that occurs at school was also interrupted during the pandemic

For children, going to school is not just about learning reading and math: it’s also about developing the social and emotional skills critical to succeeding in life. School closures eliminated some of these critically important aspects of school beyond academic activity, such as the development that occurs through personal relationships among students and between students and teachers, after-school activities that support children’s mental and emotional well-being and skills development, and a sense of routine. In addition to the cessation of their normal activities at school, during the pandemic, children have lost in-person contact with relatives and friends and have witnessed many sobering daily life realities, from parents who may be unsure where the next meal or rent payment will come from or who are working risky jobs in order to make ends meet, to family members fearing that loved ones are in danger of serious illness or even death. Overall, the crisis has helped highlight the importance of other skills that are often overlooked in the school context, but that should be nurtured as part of going to school and that will merit more attention in the aftermath of the pandemic.

A range of skills often referred to as socioemotional or noncognitive skills—including creativity, tolerance, persistence, empathy, resilience, self-control, and time management—have long been neglected in education policy, which has tended to follow the so-called cognitive hypothesis (Tough 2012; Ravitch 2011, 2020; Rothstein, Jacobsen, and Wilder 2008). 25 These noncognitive skills are deemed lower priorities in academic contexts—including skills that children typically lagging behind could have an edge in—and their integration in the usual components of learning and teaching is far from standard. As a result, when decisions about curriculum, standards, and evaluation are made, socioemotional skills tend to be the last on the priority list and the first on the chopping block, while testing highly on math and reading—skills that tend to be correlated with having more educated parents and higher household incomes—is richly rewarded in school, furthering “deficit” narratives (faulty messages about who can and cannot succeed in school, and about what succeeding in school means).

For sure, parents and teachers have long been attuned to the broad range of life skills that their students need to develop, but this crisis has sharpened that focus. The sudden need for children across the board to adapt to uncertain and rapidly changing circumstances and to cope with new levels of trauma make it all the more urgent to address this disparity between what parents and teachers understand about the breadth of skills critical to child development and systems that focus on testing a narrow set of cognitive skills. For example, resilience—the ability to adapt to and thrive in different situations—along with persistence and self-control have gained new recognition as important life skills during these months of the pandemic. Children transitioned to online learning overnight and have had to follow classes without the direct supervision of the teacher or the interactions with other students, which requires a higher than usual degree of self-control and persistence. Creativity is another skill that likely is serving children well during this crisis: Students who find new ways to keep themselves engaged and to make forced isolation productive are benefiting, while their peers who are easily bored are losing ground.

As we slowly move forward during the pandemic and we return to “normal,” it is going to be more important than ever that we do not let this recognition of whole-child development fall away and revert to a narrow focus on academics. Doing so would cause harm on several fronts. First, it would ignore and potentially exacerbate the trauma that many children are experiencing. Second, it would put low-income students even further behind—both by weighing heavily the areas of learning that they have been least able to access and by failing to recognize the natural variation in students’ strengths across a broader range of skills, or “patterns of thoughts, feelings, and behavior” (Borghans et al. 2008). And finally it would miss a unique opportunity to better balance what schools can do. Noncognitive skills are demonstrably as important as other cognitive skills when it comes to ensuring that children will thrive both in school and later in life. Moreover, since academic and socioemotional skills develop in tandem, and in recognition of the added challenges during the pandemic, it will be more critical to approach skills development holistically and make teaching and nurturing the whole child central, rather than marginal (see García 2014 and García and Weiss 2016 for a summary of this literature).

Recessions, natural disasters, and pandemics disrupt learning the most when there is no contingency planning

As noted above, prior research on circumstances somewhat similar to the shutdown during the pandemic is important to review—findings from this research may not be directly applicable due to substantial differences in the circumstances, but understanding the mechanisms through which learning occurs under these circumstances, as well as how to be prepared for the upheaval, is critical to informing our way out of this current crisis and our readiness for future ones. This is particularly the case regarding evidence from the research on “education in emergencies,” which examines the provision of education in emergency and post-emergency situations due to pandemics, other natural disasters, and conflicts and wars, generally in poor countries around the world. 26 The practical recommendations from this field have been largely ignored in the education policy arena until now, because they have not seemed to apply in the rich countries. 27 However, there are some exceptions overall and for the United States in particular, including cases of natural disasters such as Hurricanes Katrina and Maria.

The following lessons can be extracted from this research: Emergencies lead to undeniably negative impacts on educational processes and outcomes; the most disadvantaged population subgroups experience the largest, and most lasting, negative consequences; and contingency plans—absent during the ongoing pandemic—are of critical importance. Providing education, often made available because of these plans, leads to positive outcomes to children and societies. Moreover, emergencies tend to strain existing resources, adding additional challenges.

We summarize here a few key findings. For example, by the end of the school year following the devastation that Hurricanes Katrina (August 2005) and Rita (September 2005) brought to New Orleans, the performance of students who were displaced dropped by 0.07 to 0.22 standard deviations relative to what their performance would have been without the hurricanes (this range includes an average across subjects and grades calculated by Pane et al. [2008] and estimates by Sacerdote [2012] on math and reading). Principals reported that students who were displaced were judged more likely than students in the control groups to engage in negative behaviors, such as fighting, violating school rules, arguing, bullying, playing in isolation, and eating in isolation, and more likely to need mental health counseling; they were also judged less likely to engage in positive behaviors, such as participating in before- or after-school clubs or activities, school-sponsored social events outside the school day, or sports teams (Pane et al. 2008). Sacerdote (2012) also found longer-run effects, including rates of college attendance that were one to four percentage points lower relative to trends measured in cohorts not affected by the natural disasters. 28 Importantly, Özek (2020) finds that some of the negative effects of disasters on students mostly vanish after the first year when there is an “adequate compensatory allocation of resources.” Among the resources he cites as critical to compensating the negative effects of emergencies on learning are teachers—specifically ensuring that the most effective teachers are working with the most vulnerable students. Although, as noted, Özek (2020) found that first-year effects tend to decline, effects persist in the second year in high-poverty schools and in low-performing schools.

Natural disasters and recessions also create economic shocks. Research exploring the consequences of recessions such as the Great Recession sheds light on ways today’s economic crisis is likely affecting children’s education. For example, Irons (2009) discusses the ways that “unemployment and income losses can reduce educational achievement by threatening early childhood nutrition; reducing families’ abilities to provide a supportive learning environment (including adequate health care, summer activities, and stable housing); and by forcing a delay or abandonment of college plans.” Shafiq (2010) also discusses potential negative effects from economic shocks, such as long hours worked by parents, which “reduces the time that parents can devote to assisting their child with homework, reading, and other educational activities.”

Economic shocks in turn lead to cuts in education budgets. Jackson, Wigger, and Xiong (2018) show that spending cuts enacted during the last recession had detrimental effects on education outcomes: the per-pupil spending cuts that states made during the Great Recession (by roughly 7% overall, by over 10% in seven states, and by more than 20% in two states) reduced college enrollment and test scores, particularly for children in poor neighborhoods, and the impacts of these cuts were greater for Black and white students than for Latino students. Jackson, Wigger, and Xiong (2018) estimated that the impacts of such large-scale and persistent education budget cuts are very significant: a $1,000 reduction in per-pupil spending led to a reduction in test scores of about 0.045 standard deviations and a roughly 3 percentage point decline in the share of high school students who go to college. Often, recovery after a shock never fully happens, as explored in more detail later in our report.

The education-in-emergencies research underscores that “contingency plans” are critical to dealing with emergency and post-emergency situations. Specifically during crises arising from war, conflicts, natural disasters, and pandemics, children are displaced often as homes, neighborhoods, and schools are destroyed—and this may threaten survival or inflict some level of trauma upon children. 29 A certain level of preparedness is critical in order to provide an effective response at the onset of a crisis, and to “prepare, cope, and recover” (UN IASC 2007, 2015; Anderson 2020; Azzi-Hucktigran and Shmis 2020).

Although it is expected that countries and their education agencies have a plan to deal with short-run disruptions (i.e., snow days, flu season, etc.), such expectations are uncommon when it comes to contingency plans for larger, longer emergencies. Most information including guidance on planning for education in emergencies comes from several international organizations involved in major, longer-term emergencies. One exception is a reference in a White House publication reviewing assistance provided after Katrina; these words should be heeded in the aftermath of this pandemic:

Individual local and state plans, as well as relatively new plans created by the federal government since the terrorist attacks on September 11, 2001, failed to adequately account for widespread or simultaneous catastrophes.…The President made clear that we must do better in the future. The objective of this report is to identify and establish a roadmap on how to do that, and lay the groundwork for transforming how this Nation—from every level of government to the private sector to individual citizens and communities—pursues a real and lasting vision of preparedness. To get there will require significant change to the status quo, to include adjustments to policy, structure, and mindset. (The White House 2006)

As has been evident in the past few months, there was no national education plan in place to deal with medium-run or long-run emergencies for the scale of COVID-19. Existing plans (as indicated, outlined by international organizations) offer “contingency planning tools” to ensure appropriate arrangements are made to analyze the impact of potential crises and to respond in a timely and effective way. The strategies suggested are characterized as flexible learning approaches, which reflect the reality that the circumstances and needs vary widely. Continued provision of education is expected to support both learning and the psychosocial well-being of both students and educators (Anderson 2020). Some strategies aim at promoting cognitive, emotional, and social development through structured, meaningful, and creative activities in a school setting or in informal learning spaces that replace the unavailable traditional schools. In other words, these programs are designed to provide support similar to that provided by good school systems on a regular basis. 30

Clearly, there are potentially relevant aspects of research on emergency education that, where emergency education resembles the COVID-19 situation, could help policymakers identify what needs to be done immediately and going forward to help schools and students recover. Before we discuss these, we devote much of the next section to assessing how this crisis is expected to have worsened impacts on vulnerable subgroups, and to exacerbate inequities overall.

How is COVID-19 exacerbating opportunity gaps (and what steps are schools taking in response)?

The COVID-19 crisis has exacerbated the well-documented opportunity and enrichment gaps that put low-income students at a disadvantage relative to their better-off peers. By opportunity and enrichment gaps, we mean gaps in access to the conditions or resources that enhance learning and development between low-income students and their higher-income peers (with low-income students less likely than their better-off peers to access these conditions and resources). Before we delve into the details, it is important to state that this should not come as a surprise. The baseline operating status of the education system in the United States before the pandemic had severe problems with regard to equity. Put simply, as a nation, we have structured the education system to deliver the disparate outcomes that it delivers, i.e., outcomes that differ by social class, minority status, and other student characteristics: “It’s not a coincidence or accident” (ASI 2020). 31 Here we briefly describe a few of the gaps that are most directly relevant to students’ abilities to learn during the pandemic: basic needs, economic relief, and support for families and health. We also discuss how the pandemic has exacerbated the limitations of standardized assessments, especially when used to measure performance gaps in education.

There are two important caveats to this discussion. First, any recent statistics are preliminary (and likely quite conservative). Second, there are, of course, other gaps that we are not able include here—for example, in wealth through homeownership or toxic stress linked to structural racism (Lerner 2020; Morsy and Rothstein 2019)—but that are interacting with and compounding those factors that we are able to examine. As leading education and civil rights organizations summarizing the breadth of the opportunities and enrichment gaps note, “the transition to educating students in their homes or shelters has exposed and exacerbated inequities in education, food security, and housing that have long existed” (AFT, LDF, and Leadership Conference 2020). We add health and mental health to that list, and we emphasize the critical role schools play as part of the social safety net and as the first responders to children’s basic needs (Kirk 2019; Weiss and Reville 2019; ASI 2020).

The pandemic has exacerbated opportunity gaps associated with uneven access to food and nutrition, shelter, health insurance, and financial relief measures

The disruption caused by the pandemic and the interruption of the normal operation of schools continue to pose barriers to meeting the most basic of children’s needs (access to food and nutrition and shelter). Families’ resources also have been largely impacted by the economic downturn that followed the disruption. There is overwhelming evidence that low-income children and their families have much less access to nutrition and shelter, that children of color and children from immigrant families are disproportionately affected, and that this lack of access has palpable consequences for their development. It is no secret that the inequities are built into our economic and policy setups, and that these inequities affect children’s development as well. The school shutdowns and economic crisis caused by the pandemic are exposing and exacerbating these challenges.

Evidence on expanded opportunity gaps due to lack of access to food and nutrition

In 2013, as the United States was still recovering from the recession of 2007–2008, half of all public-school students were eligible for free or reduced-price school meals (SEF 2015; Carnoy and García 2017). In other words, years into the economic recovery, a record share of one in two public-school students lived in a household that was unable, absent government support, to consistently feed them. With millions of adults newly out of work due to the economic shock of the coronavirus pandemic—and federal relief insufficient, slow, and difficult to access—many more children are now in food-insecure homes (i.e., they have limited or uncertain access to adequate food, as measured by responses to survey questions about access to food).

Using data from the new Household Pulse Survey (HHPS) from the U.S. Census Bureau, 29.8% of respondents with children were food insecure (Schanzenbach and Tomeh 2020). Bauer (2020) estimates that there were almost 14 million children living in a household characterized by child food insecurity during the week of June 19–23, 2020, “5.6 times as many as in all of 2018 (2.5 million) and 2.7 times as many as during peak of the Great Recession in 2008 (5.1 million).” 32

The data about food insecurity is backed up by news reports showing record levels of visits to food banks during the early part of the pandemic and the shortage of resources to meet the demand for food. According to Feeding America, one in seven Americans relied on food pantries before the pandemic, with demand doubling or tripling in many places in the first weeks of the crisis. By late April, less than two months into the pandemic, food pantries in Chicago and Houston were almost out of staples, and one third of New York City’s food banks had closed due to lack of supplies, donations, and/or volunteers (Conlin, Baertlein, and Walljasper 2020).

Schools continuously tried to fill the void to the extent they could, with buildings that were closed for instruction reopening as places to collect, prepare, and distribute meals. Some schools were serving breakfast or dinner or are giving out weekend meal “packs” for students, and many provide meals for older and younger siblings as well. For example, schools in Anne Arundel County, Maryland, served an average of 8,000 meals—three per day—for the first 39 days of the pandemic, hitting the one million mark on May 12. District Superintendent George Arlotto said of the importance of supporting his students, “We know if we’re not serving meals they might not be getting fed, at least certainly not three meals a day” (Streicher 2020).

However, difficulty matching meals to parents’ schedules and lack of sufficient transportation to deliver meals limited many districts’ ability to serve the students they normally serve. Across the Denver metro region, district capacity during the first month of school closure starting in March spanned a wide range, serving just 12% of students in the largest and lowest-income district, Denver; 16% in Jeffco; 34% in Aurora; and 57% in the Adams 12 Five Star Schools district (Meltzer, Robles, and LaMarr LeMee 2020).

Across the country overall, the networks set up to provide meals left out a large proportion of children. “Only 61.0% of parents whose families received free or reduced-price meals during the school year reported receiving school meal assistance during closures,” noted Waxman, Gupta, and Karpman (2020), who also found that 17.2% of parents living with children under age 19 reported receiving charitable food in May 2020.

Evidence on expanded opportunity gaps due to lack of access to shelter

In addition to children who are especially vulnerable during the pandemic because they rely on schools for basic food and nutrition are children who are homeless. Data show that before the pandemic began, large numbers of students in districts across the country were homeless. 33 For this numerous group of students, getting an education remotely is unthinkable. With millions of adults newly out of work due the economic shock of the coronavirus pandemic—and eviction bans expired or expiring in localities around the country—unstable housing is putting the challenges of educating homeless students into starker relief. Some school districts are paying attention to the needs of their homeless students. In San Jose, California, for example, some schools are expected to be open for counseling and in-person instruction for homeless and special needs students (Lambert, Burke, and Tadayon 2020). The United States Interagency Council on Homelessness (USICH 2020) has issued some general guidelines as to how school districts can work with local public health officials and community partners to identify temporary, safe, and stable shelter options for families or youth experiencing homelessness who must quarantine. The agency also provides guidance on ensuring homeless children’s access to remote education while schools are closed.

Evidence on expanded opportunity gaps due to unstable employment and lack of access to financial relief and health insurance

Loss of work has hit families across the board, as initial unemployment shocks in the travel and entertainment industries expanded to shut down restaurants, retail, and even some of the health care sector shortly after the pandemic started. While some of those jobs have returned, we still have extremely elevated rates of unemployment and loss of health insurance. And low-income parents are in particularly tough situations because of the low-paying and unstable nature of their jobs. Those who lost already-precarious non-standard jobs (like “gig” work and other independent contracting work) don’t qualify for unemployment insurance (and many had trouble accessing emergency unemployment benefits because of outdated state systems). Further, many workers around the country who had job-related health insurance lost it just when they needed it most (Cooper and Worker 2020; Bivens and Zipperer 2020). While Congress passed relief measures earlier in the pandemic, some key components of relief—such as the extended unemployment benefits—have expired, and further measures are at this writing stalled in Congress (Gould 2020a; Shierholz 2020). Not granting the needed economic relief and not granting more support for families is going to add to the challenges of parents who have dual responsibilities of supervising children’s learning and putting food on the table and providing them with health protection.

Evidence on expanded opportunity gaps due to health challenges for families

The pandemic obviously also raises the possibility that children’s families and children themselves are grappling with illness and even death. Research shows that the health risks are higher for workers in low-paying professions than for workers in high-paying professions because the former are much less likely to be able to work remotely (Gould and Shierholz 2020). Moreover, essential workers—such as warehouse stockers, home health aides, and delivery and trash truck drivers—now risk contracting COVID-19 while still struggling to survive on low wages. 34

Thus it is not surprising that this crisis has also resulted in an increase in the number of children who face the serious illness or death of a relative. It seems likely that a large share of low-income students and Black and Hispanic students now resuming schooling have suffered major trauma. With Black students losing family members in disproportionate numbers, the pandemic is exacting a particular toll on these communities (Harper 2020). For example, in Georgia, where African Americans make up just 30% of the state’s population, they represent over 80% of COVID-19-related hospitalizations and more than 50% of deaths (Weiner 2020). When New York City was the epicenter of the pandemic in the United States, the heavily white borough of Manhattan had a hospitalization rate of 3.31% and a death rate of 1.22%—the city’s lowest—despite having the oldest residents of any of the city’s five boroughs, while the heavily low-income, African American borough of the Bronx had the highest rates, 2.24% and 6.34%, roughly double those of Manhattan (Wadhera et al. 2020). 35

Evidence on expanded opportunity gaps due to health challenges for students

These same groups of students—Black and Hispanic students, and low-income students— suffer academically due to physical and mental health problems that are less likely to be addressed in a timely and consistent manner (Ghandour et al. 2018; Menas 2019; Morsy and Rothstein 2019). Many rely on school-based health clinics, a critical resource that is no longer available in schools where teaching is not occurring on site. Earlier in the pandemic when access to doctors’ offices was severely limited (with many serving only urgent cases) and hospitals were overwhelmed (and perceived as unsafe), problems from toothaches and ear infections to emotional breakdowns went untreated and, in many cases, became much worse. When the state of Florida shut down in late March, for example, it banned all nonemergency medical and dental services, leading to questions as to whether even check-ups conducted prior to procedures were permitted (Boca News Now 2020). 36

With both physical and mental health on the line for stressed-out students, school districts are trying to leverage newly available resources to compensate. These include additional Medicaid resources provided in the first federal COVID-19 relief legislation, the Families First Coronavirus Response Act. That act temporarily increases the federal Medicaid match to states that agree to maintain current eligibility standards and cost-sharing requirements and limit disenrollment. Relaxed guidelines enable states to use some of that money for telehealth services without additional authorization, so students can see doctors remotely as needed. The federal CARES Act that was enacted in March provides $13.2 billion for K–12 schools as part of Title I funding, and it includes several aspects of student health in allowable uses. The Los Angeles Unified School District has used some of that funding to launch a mental health hotline for students. Superintendent Austi Beutner notes, “Their world has been turned upside down and we need to make sure students have the support they need [during this crisis]” (Jordan 2020a).

All of the above challenges, of course, mean more stress. And for children who were already living in cramped and less-than-ideal situations, having all family members in the house makes the regular challenges of daily life much greater. Increased incidences of abuse due to confinement, stress, and lack of access to outside support further affirm the urgency of addressing the stressors that are affecting families and, in turn, their children’s development and ability to learn (Stratford 2020; Greeley 2020; Tolerance Trauma 2020).

The pandemic has exacerbated opportunity gaps in teaching and learning

It is in these challenging contexts of economic insecurity and housing instability that students (and teachers) were suddenly transitioning to remote learning, adding another class- and race-based disparity in education opportunity: the “digital divide.” The “digital divide” refers to the fact that some children do not have access to the devices or internet services needed to operate online—and there is a double digital divide that arises from the fact that low-income children and Black and Hispanic children are more likely to lack this access (García, Weiss, and Engdahl 2020; Tinubu Ali and Herrera 2020). Research on the digital divide counters the idea that all children can access online instruction and the education system shifted to online education. Given the resurgence of COVID-19 cases over the summer and the growing number of school districts announcing plans to begin the 2020–2021 school year totally remotely, the divide would only continue in the imminent future. Some low-income families are struggling to obtain a computer or other device for each child, with a share of families lacking an internet connection enabling children to do assigned work online or a quiet space to do solo work (let alone attend the Zoom calls that classrooms are now conducting; see Hodges et al. 2020).

Our analysis of data from the 2017 National Assessment of Educational Progress shows that digital devices are not universally available or used at home for school-related purposes. Our findings are presented in Figure D . Specifically, 84.4% of eighth graders overall, and 76.3% of poor eighth graders have a laptop or computer, which means that about 16% of eighth graders and 25% of poor eighth graders have no desktop or laptop at home. In addition, only about half of eighth graders had experience using the internet at home frequently for homework, with a much larger share of non-poor students (56.1%) than poor students (46.4%) accustomed to using the home internet frequently for homework (a gap of 10 percentage points). (We define poor students as students who are eligible for the federal free or reduced-price lunch programs, and non-poor students as students who are ineligible for those programs.) 37

Not all students are set up for online learning, and students who are poor have less access to key tools : Share of eighth-graders with access to online learning, by income level and tool, 2017

Notes:  Poor students are students eligible for the federal free or reduced-price lunch programs. Non-poor students are students who are ineligible for those programs. Frequent use of internet at home for homework means every day or almost every day. Students’ teachers were either “already proficient” in, “have not” received training in, or “had received training” in “software applications” and “integrating computers into instruction” in the last two years.

Source:  2017 National Assessment of Educational Progress (NAEP), eighth-grade reading sample microdata from the U.S. Department of Education’s National Center for Education Statistics. Chart adapted from Figure D in García, Weiss, and Engdahl 2020.

Our analysis of 2017 NAEP data also shows that teachers are not universally prepared to teach online, as also shown in Figure D. Just about a third (32.5%) of eighth graders overall have teachers who consider themselves proficient in using software applications, and only a fifth (19.3%) have teachers who consider themselves proficient in integrating computers into instruction. The shares of students overall with teachers who don’t consider themselves proficient but who have received some training in applications and in computer use in instruction are higher (43.4% and 69.2% respectively). Yet that still leaves nearly a quarter (100% minus 43.4% minus 32.5%, or 24.1%) of eighth graders with teachers who are neither proficient in nor trained in software applications, and close to one in eight (100% minus 69.2% minus 19.3%, or 11.5%) with teachers who are neither proficient in nor trained in how to integrate computers into instruction.

A Southern Education Foundation report on class- and race-based disparities during the COVID-19 crisis finds similar disparities in access to the resources needed for online learning. It notes that nearly one in five African American children and a slightly greater share of children in low-income households have no access to the internet at home (Tinubu Ali and Herrera 2020). These disparities mirror those reported by superintendents who responded to a survey by AASA, the School Superintendents Association, in late March as schools across the country were closing down (Rogers and Ellerson Ng 2020). 38 Numerous news outlets reporting on the digital divide have also noted these disparities by race and ethnicity (for example, see Kamenetz 2020b). School shutdowns and associated internet- and device-access challenges have been occurring at a time when many of the public libraries that have been a resource for families without computers or home internet access are closed due to the pandemic.

School districts are trying hard to take these challenges into consideration and to make up for the large disparities they know their students face. Some, like Montgomery County, Maryland, are sending home Chromebooks and tablets, prioritizing students who are eligible for free- and reduced-price lunches or are known not to have devices at home (St. George 2020). Others, like New York City, are lending iPads to students who need them (NYC Department of Education 2020). All of this takes time, however, and many districts lack the resources. (Montgomery County provided paper packets to students for the first few weeks of closures, until it could distribute the Chromebooks.) Some districts are making online work optional, as a way to not further disadvantage students who physically cannot do it, but of course that can weaken schools’ capacity to continue to instruct.

Tinubu Ali and Herrera (2020) also report on dozens of innovative strategies districts have employed to overcome some of these disparities. These strategies include deploying roving school buses that add Wi-Fi coverage in South Carolina, the purchase of thousands of additional hotspots in Texas, and two months of free internet in Caldo Parish in Louisiana thanks to a partnership between Comcast and the local NAACP. (Comcast is also providing free access in Montgomery County, Maryland.) In Tennessee, Staples is printing and distributing printed materials free of charge to students who cannot afford the cost, and public schools in Jackson, Mississippi, are developing a package of learning materials that are paper-based or online and shared via the state’s educational programming television channels. South Carolina’s public television network is providing free virtual professional development sessions on home learning and technology best practices. In Miami-Dade, one of the most diverse school districts in the country, instructions for families are provided in English, Spanish, and Creole.

The pandemic has exacerbated the limitations of standardized tests

Digital divides and disparities in parental resources are fueling the growth of opportunity gaps that likely will make it harder for disadvantaged students to engage with their schoolwork and easier for these students to lose interest in school. If so, the pandemic will also widen performance gaps between disadvantaged students and their better-off peers and increase graduation and school dropout rates among disadvantaged students, particularly if districts don’t adjust practices to reconnect with these students.

Thus, one practice that may need adjusting or revisiting is testing. During the pandemic, traditional assessments—which have limited value even in normal contexts—are much less useful in capturing what students know and have learned. These assessments could feel “overwhelming or condemning to children” at a time when it is necessary to create opportunities for students to show what they know and to demonstrate where they are, and for teachers to adjust instruction to students’ current development in order to advance their development and potential (RESEARCHED 2020, NPE 2020). As set forth above, students have very uneven access to the online resources they need to take tests, let alone complete them effectively. Similarly, students have uneven access to the special instruction and supervised practice that help students pass these tests—with lower income students and Black and Hispanic students less likely to have access than their higher income and white peers. This means that standardized testing during the pandemic will deliver results that are, by design, going to be even more closely correlated with life circumstances than is true during periods of regular classroom instruction. Compounding all of the barriers to meaningful and equitable monitoring and testing during the pandemic, teachers in remote settings lack the tools that they have when they are in their classrooms to interpret test results. In other words, in a classroom, teachers are more able to distinguish between a low score likely due to the student’s lack of understanding of the material versus a low score due to the student’s frequent absences, emotional distress, or other factors. As a result, teachers working remotely are hard-pressed to respond to a test score with an appropriate strategy to support the student.

For all of these reasons, traditional standardized tests have limited value in this context and may do more harm than good. 39 Rather, school districts should be using tests that are designed to assess where students are across a range of areas and to help teachers meet students there. These tests include diagnostic tests, formative tests, SEL assessments, and assessments that can be performed remotely such as project-based assessments and capstone projects. 40 These types of tests will be critical to helping students and teachers alike start to dig out of the academic hole dug by the COVID-19 shovel.

Going forward: Translating what we have learned into a plan for the “three Rs” of relief, recovery, and rebuilding

Throughout the coronavirus pandemic, we have made choices about how to sustain, or provide relief to, the education system. We have also had the opportunity to consider how best to proceed as we start to recover, and how to rebuild the system by taking more decisive action on substantial, long-needed changes. Indeed, how well we rebuild the education system will determine how well we address the impacts the pandemic has had on our human capital and how prepared we are for shocks of this nature in the future.

As noted above, students have seen their normal learning and development interrupted and disrupted. Inevitably, this will lead to lost ground during the pandemic, with disadvantaged students particularly vulnerable given the way that the pandemic has compounded large existing opportunity gaps. We propose a set of targeted education interventions and comprehensive services to lift up disadvantaged children and reduce inequities as we move out from this pandemic. This plan tackles today’s three Rs — relief, recovery, and rebuilding —with a phased three-stage process that must be properly funded at each stage.

Specifically, this three-pronged plan requires making the necessary investments to 1) put school systems on a solid footing to provide effective remote instruction and supports at scale as the crisis continues to play out (the “relief” phase); 2) make new investments to help schools and students compensate for lost time and ground during the period of quarantine (during the “recovery” phase); and 3) lay the foundations for a shift toward an education system that understands the complexity of education production and its multiple components, untaps children’s talents, works equally for all students, and reflects the value we place on education as a society (in the “rebuilding” phase). This plan will require substantial amounts of resources and strong collaboration and effort.

If the Great Recession is any indicator, competition for resources will be fierce. In fact, early indicators are that this public health crisis will pose enormous challenges for states and local governments, those responsible for over 90% of the school systems’ revenue. 41 Moreover, we entered this crisis in a more difficult position than in the Great Recession (based on a comparison with what we learned from the 2009 federal stimulus, and from the fact that about half of the states as of 2016 had yet to return to the level of per-student spending that they had attained prior to the Great Recession). 42

With state budgets at historic crisis levels and the economy continuing to struggle, 43 the prevailing narrative will likely be an even more severe version of “we can’t afford that” than what we experienced in the aftermath of the Great Recession. It will therefore be more important than ever to meet that assertion with the fact that “we can’t afford not to.” All of the evidence we have amassed demonstrates that not spending costs far more, and delivers far less, in the long run, than making the needed investments. 44

Underlying the fiscal barriers to making the needed investments in education is a lack of leadership at the federal level that makes it very difficult for states to do what is needed. So far, there has been insufficient, scattered attention to education from policymakers, but even that has had a marked political tone that fails to acknowledge challenges or provide required resources. 45

Relief: Give schools urgent resources so that they can provide effective remote instruction and supports at scale during the pandemic

During the pandemic, schools have been challenged with not only fulfilling their main roles of educating our children but also serving as a key part of the safety net: Specifically, to some degree, schools have provided not just remote education but also supports like meals, health services, counseling, and, in some cases, housing. Given the fact the schools are not universally going to be resuming standard operating procedures in the foreseeable future, policies must be enacted to enable all schools to provide effective remote instruction and supports consistently, and at scale.

While states and school districts are critical players in the relief stage, most of the calls for action involve the federal government because states and school districts are not only overstrained but also facing imminent budget cuts caused by the pandemic, with an inability to incur deficit spending.

Congress must resume consideration of additional relief measures and pay more attention to schools and associated public supports, including child care, social services, food and nutrition supports, and physical and mental health care—devoting substantially larger shares of, and sufficient, funding to these needs. At a minimum:

• Every school must be equipped and have the necessary resources, in conjunction with both public and private community institutions, to feed children (and, as relevant, their families) for as long as the current crisis demands.
• These needed services include the various wraparound supports specific to physical and mental health services, and to countering the various negative impacts of the crisis on the mental and emotional health of both students and educators.
• During the first months of the pandemic, the lack of preparation to cope with the lockdowns meant that many children lost access to the most basic needs. School districts must coordinate with state and local agencies and partner organizations to assess students’ needs so that districts understand their students’ situations and can respond accordingly.
• Unlike during the first months into the pandemic, access to online education must be universal.
• Schools must be equipped to do needs-based monitoring of students’ status in terms of internet access; their access to computers and other technology tools for online learning; and students’ capacity to make effective use of the tools they have. This type of diagnostic assessment of technology and access is critical to understanding the degree to which students can engage with instruction on a regular basis and is foundational to their ability to learn.
• District and school leaders should provide teachers with the necessary training and preparation to avoid unstructured instruction and the kind of “trial-and-error” instruction many had to employ during the first months of the pandemic.
• District and school leaders should survey teachers as to the specific professional development and other supports they need to teach effectively in these adapted contexts, and Congress should allocate federal aid to ensure that all teachers obtain the needed support. 47
• Given that many teachers, like other “essential workers,” must balance instruction with attending to other household realities, including parenting their own children, Congress should ensure that support for child care is included in key relief measures. 48

In the “relief” phase, schools must also have the resources they need to safely operate with partial on-site instruction if the health protocols allow for doing so.

• These plans at the very least must include communicating, educating, and reinforcing appropriate hygiene and social distancing practices in ways that are developmentally appropriate for students, teachers, and staff; maintaining healthy environments (e.g., cleaning and disinfecting frequently touched surfaces); repurposing unused or underutilized school (or community) spaces to increase classroom space and facilitate social distancing, including outside spaces, where feasible; developing a proactive plan for when a student or staff member tests positive for COVID-19; conducting case tracing in the event of a positive case; etc.
• Every school district must receive the resources to ensure the safety guidelines are disseminated, understood, and followed. Ensuring that guidelines are followed includes providing the financial resources and the equipment so that members of the school community are protected, the facilities are cleaned, and staff members have what they need to be safe. 50

Recovery: Provide extra investments to help students and schools make up lost ground as they return to in-school operations

When schools resume their operations back in the classroom, it will be critical to fully understand which students have been engaged and to what degree, how much they have learned, and where they have fallen behind. But for meaningful teaching and learning to take place, educators must first be able to assess their students’ well-being and readiness to learn. Once they achieve that, educators will need sufficient, appropriate resources and tools to enable students to catch up and continue their development.

• Careful use of well-designed diagnostic tests will be critical to preparing and equipping schools and teachers to do their jobs, which will include adjusting instruction as necessary, and thus to helping students make up for disrupted education.
• Using diagnostic assessments to assess the needs of the pandemic can provide a model for using assessments more appropriately in the future—i.e., as formative and informative tools of teaching and learning, rather than as evaluative tools of judgment. 52
• Educators must receive training not just on diagnostic testing but also on benchmark testing, project-based learning, capstone projects, and performance assessments, with a focus on remote instruction and trauma-based instruction. 53
• COVID-19 is expected to boost early retirements, especially among teachers who are closer to retirement and among those in the highest-risk groups, and voluntary attrition, especially among those teachers who faced major obstacles in their work during the first months of the pandemic. These risks could also affect other staff at schools (e.g., nurses, paraprofessionals, principals) and come at a time when more personnel are needed. Budget constraints could further deplete the teaching and education workforces. 54
• Flexible approaches will be necessary: Children learn differently, and they underwent different challenges during the pandemic. Remote learning is less effective for children who are less prepared (i.e., without full access to computers and other equipment, without experience using devices for school work, with fewer supports, and with less likelihood of being engaged).
• More intensive interventions and strategies will be needed for students identified as at heightened risk of dropping out altogether.
• Providing more flexible and personalized interventions for students will require more, better, and targeted investments in professional development for teachers so that they are equipped to deliver personalized learning.
• The coronavirus crisis created serious challenges to students’ well-being and development that require a response focusing on their social and emotional learning, health, and well-being. 55
• Through their positive relationships with students, and through more specialized knowledge about social and emotional learning (SEL), teachers can contribute to the social and emotional learning of students. Therefore, improving training and support for teachers, teachers’ aides, and other school staff members in SEL will be critical to helping students regain their footing after the coronavirus crisis.
• Supporting students’ social and emotional development will also require increasing the number of school nurses (clinics), counselors, social workers, paraprofessionals, etc., with a focus on both students’ social and emotional learning and their mental and physical health. Other practices at school (curriculums, etc.) can be enhanced to support social and emotional learning.
• Schools should consider increasing both the amount and quality of learning time through a number of options, including extended schedules (in particular for those students lagging behind), summer enrichment programs that support the whole child, and staffing strategies that reduce class sizes and staff schools with sufficient and highly credentialed educators, 56 including teachers’ aides and tutors, whether in person or online.
• Schools should also consider ensuring access to and quality of online instruction, if online education is going to be used on its own or in conjunction with traditional instruction. In keeping with the recommendations in the “relief” section above, online instruction needs to be better tailored (especially for those who are least prepared), of high-quality, and accessible to all students. Similarly, schools need to provide supports for teachers who had not been prepared on how to use technology for instruction. Teachers should be enlisted in helping to create online instructional tools and policies. 57 Finally, districts and teachers must apply “an equity lens,” to target tools and resources to students who experience the biggest opportunity gaps (i.e., students who lack digital access or who suffer more from nutrition challenges or housing instability).

Rebuilding: Redesign the system to focus on nurturing the whole child and on equal provision of opportunities

Major crises provide unique opportunities to rethink the status quo. In the aftermath of the coronavirus crisis, policymakers must seize the opportunity to address structural problems in the educational system and invest new and different approaches. This should be a pathway toward establishing a system that ensures we meet the student, teacher, and school needs that we have been neglecting and make delivering excellence and equity in education the norm. Delivering equity in education requires addressing the major disparities in student outcomes by race and social class that arise in a system designed to deliver disparities in educational opportunities. The bottom line is, we must seize this moment to redesign the system to deliver the excellence and equity needed for every child to be able to thrive. 58

• Going forward, the education system must better balance what we teach, how we teach it, and how we reward the full range of skills that matter for and define a child’s development and education. The institutions that create education policy and practice must make many changes to ensure that schools teach and reward the development of cognitive and socioemotional skills. The shift begins with recognizing that skills of both types are mutually supportive, not mutually exclusive. 59
• For example, a whole-child approach that embraces and employs a broader range of assessments, and uses these assessments for “formative and informative” purposes, rather than for judging and sorting students, would also go a long way to closing the gaps. This shift recognizes that traditional tests are designed to capture only a narrow slice of what children know and can do, and that these tests are biased toward the types of skills that are closely correlated with parents’ socioeconomic status, not necessarily, and not exclusively, children’s potential.
• School districts must conduct a detailed needs assessment of the district overall and of each school in the district, identifying where poverty and all other stressors that are intertwined with poverty impact the ability of children to learn, and mapping out community resources that can be leveraged to meet those needs. And it means working through a variety of channels (and with a variety of partners) to close the opportunity and enrichment gaps that have long impeded progress for low-income students, students of color, and students from immigrant families and communities. 60
• Education systems must tackle head-on the school- and district-based disparities that mirror and compound the disparities that children experience at home. In high-poverty schools, and in schools serving larger shares of minority students, there is generally less access to the education “inputs” that lead to good outcomes, whether it is highly credentialed teachers, access to after-school programs, access to AP classes, positive ways of dealing with discipline issues, etc. A broad range of tools and resources must be deployed to close gaps by types of school on all fronts, making education funding more adequate and more equitable.
• School systems and their community partners must also establish a flexible set of strategies to offer wraparound supports—such as health clinics, community gardens, and parenting classes—tailored to the specific features of the community and the diversity of the communities serving our 55 million students across the country.
• All the institutions in the education system and society at large must value education and educators and treat teachers as professionals. Teachers’ judgement is critical to identifying what children and educators need. School districts and education institutions must improve the types and usefulness of the professional development and supports offered to teachers, to allow them to keep up with advances in research on effective teaching and face the challenges of the job. Teachers must also be given more of a say in the decisions affecting their jobs and careers, from the materials they use in their classrooms to the types of training they receive. Valuing educators also includes paying them at a level commensurate with what similar college-educated workers earn in other professions. Research shows that taking these steps can help attract professionals to teaching as a career and help prevent them from retiring or quitting their schools and the profession. 61
• Policymakers must recognize that education policy alone cannot ensure that all children have the foundation they need to get a good education. We need an economic agenda to accompany the rebuilding that lifts all children up and closes the opportunity gaps that are educational and not educational in nature. Children in low-income families—often children of color—lack many of the resources that their higher income and white peers have, which puts them at a disadvantage before they even enter their classrooms. Some opportunity gaps can be addressed by strengthened education policies. But the ones of a different nature would call for better public policies and a stronger economic agenda. 62
• Finally, policymakers at all levels must establish and fund contingency plans for the next time we experience a crisis as disruptive and overwhelming as the coronavirus pandemic, whether that occurs in the next handful of years or further into the future.

Despite the fact that we do not know exactly how the COVID-19 pandemic is affecting children’s needs and academic performance, we know enough from existing research on learning during somewhat comparable educational experiences, and from news and observations of how education is being produced during the crisis, to assess the likely consequences on educational outcomes both overall and for relatively disadvantaged subgroups.

We reviewed the research on what to expect when children experience a substantial loss of learning time, when schools make a sudden shift to remote learning and home schooling without meeting the conditions for their effectiveness, and when circumstances lead to a massive increase in stress and disruption for children and their families. We also reviewed evidence that has emerged during the crisis on the multiple challenges that children, their teachers, schools, families, and communities face, all of which exacerbate opportunity gaps. Indeed, the evidence points to disparities in opportunities that exacerbate existing inequities and place major stress on low-income students and their teachers, in particular. Due to the digital divide and many other factors, these children are most likely to lose more substantial learning time. And their families are also most likely to experience compounded stresses—such as job loss, the loss of health care, the lack of paid sick leave, the lack of child care, and the need to work on site in “essential” jobs that put them at health risks: all these factors make it much harder for these families to attend to children who are suddenly home schooling and struggling with ad-hoc efforts at remote learning.

Together, the lessons learned point to the need to enact an agenda that lifts up children and reduces educational inequities after the interruption to schooling due to the coronavirus is over. The agenda must also rebuild the system so that lifting up children and reducing inequities in education become the new norm. To accomplish this, we outline a three-stage response. The first stage is immediate relief for students and educators so they can function better in the early 2020–2021 school year as remote learning continues in some form for many children. The second stage is significant short-term investments during the recovery that will enable students whose education was interrupted by the coronavirus crisis to catch up and continue their development. The third stage is longer-term reforms to rebuild the education system so that the challenges documented here are corrected and the system finally delivers an excellent, equitable education to all children.

In the rebuilding phase, it is essential to establish an education system that embraces a whole-child approach, addresses the impacts of poverty and inequality on students’ capacity to learn and on teachers’ abilities to do their jobs, offers a flexible set of wraparound supports to mitigate the impacts of the inequities that are built into the system, values education and educators, and creates viable contingency plans for future crises.

In closing, the ultimate consequences of the pandemic for K–12 education in the United States will indeed be a function of the quality, intensity, and comprehensiveness of our response to counter the pandemic’s negative lasting effects. Indeed, our call for relief, recovery, and reform has a historical precedent. As Darren Walker, president of the Ford Foundation, recently noted:

During the Great Depression, President Franklin Delano Roosevelt affirmed the need for relief, recovery, and reform—in that order. Today, we must follow these same steps—beyond reform to a broader, deeper reimagination of our society. (Darren Walker 2020).

This societal reimagination certainly encompasses a reimagination of our education system. With the right vision, we can actually ensure that public education plays a critical role in restoring the human and social capital in our country and in readying us for the next challenges, big or small, that we may confront in the future. Our children and our future depend on it.

About the authors

Emma García  is an education economist at the Economic Policy Institute, where she specializes in the economics of education and education policy. Her research focuses on the production of education (cognitive and noncognitive skills), evaluation of educational interventions (early childhood, K–12, and higher education), equity, returns to education, teacher labor markets, and cost analysis in education. She has held research positions at the Center for Benefit-Cost Studies of Education, the Campaign for Educational Equity, the National Center for the Study of Privatization in Education, and the Community College Research Center; consulted for MDRC, the World Bank, the Inter-American Development Bank, and the National Institute for Early Education Research; and served as an adjunct faculty member at the McCourt School of Public Policy, Georgetown University. She received her Ph.D. in economics and education from Columbia University’s Teachers College.

Elaine Weiss  is the lead policy analyst for income security at the National Academy of Social Insurance, where she spearheads projects on Social Security, unemployment insurance, and workers’ compensation. Prior to her work at the academy, Weiss was the national coordinator for the Broader Bolder Approach (BBA) to Education, a campaign launched by the Economic Policy Institute, from 2011 to 2017. BBA promoted a comprehensive, evidence-based set of policies to allow all children to thrive in school and life. Weiss has co-authored and authored EPI and BBA reports on early achievement gaps and the flaws in market-oriented education reforms. She is co-author of  Broader, Bolder, Better , a book with former Massachusetts Secretary of Education Paul Reville published by Harvard Education Press . Weiss came to BBA from the Pew Charitable Trusts, where she served as project manager for Pew’s Partnership for America’s Economic Success campaign. She has a Ph.D. in public policy from the George Washington University Trachtenberg School and a J.D. from Harvard Law School.

Acknowledgments

The authors are grateful to EPI Publications Director Lora Engdahl for having edited this report, as well as for co-authoring one of the pieces this report builds on, and for her suggestions on news reports that provide useful context. To the last point, we also acknowledge the extensive work on the repercussions of COVID-19 for education conducted by many of our colleagues, of which we are only able to cite a fraction. We appreciate EPI Vice President John Schmitt’s supervision and support of this project, EPI Research Assistant Melat Kassa for her assistance with the tables and figures, and EPI’s communications staff for their assistance with the production and dissemination of this study.

1. For references on production of education, see Coleman et al. 1966; Hanushek 1979; Todd and Wolpin 2003.

2. Note, too, that we do not offer an in-depth review of these very extensive bodies of work, but rather use them to better understand what it is at play and to frame what we should anticipate the next-phase and post-pandemic outcomes to look like.

3. Students in grades kindergarten and first, for example, experienced larger gains as measured by the ECLS-K assessments in math and reading between the fall and the spring of those years. For example, our descriptive analysis of the ECLS-K 2010–2011 data suggests that students gain an average of 0.7 SD in kindergarten. For a discussion on spring to spring gains by grades (average of 0.45 SD across grades), see Bloom et al. 2008.

4. These kinds of challenges and trade-offs may also be relevant to the decisions schools will need to make for 2020–2021. For example, von Hippel (2020), when discussing school instruction that spans 12 months, explains that although year-round calendars increase summer learning, in most cases they reduce learning at other times of year, so that the total amount learned over a 12-month period is no greater under a year-round calendar than under a nine-month calendar.

5. Assessing a seminal study by Alexander, Entwisle, and Olson (2007), based on a sample of Baltimore students who were tracked from first grade in 1982 to age 22, Kuhfel explains that most of the test-score gap by socioeconomic status (SES) in ninth grade was explained by “differing summer experiences in the early elementary years.”

6. The more recent research also discusses several technical challenges that would require some concern about the findings. For example, there were characteristics of the tests used to assess skills before and after the summer that made them not comparable, or that made the tests more difficult in the fall than in the spring; very small samples in particular contexts; and other caveats. See von Hippel and Hamrock (2019) and von Hippel, Workman, and Downey (2018).

7. Atteberry and McEachin (2020) find that slightly over half of the students lose nearly all their school-year progress but the rest of the students actually maintain their school-year learning. Kuhfeld (2019) similarly finds that the summer loss is not generalized, but points to a larger loss overall, with around 60–80% of students losing ground in the elementary school grades (and an even larger share with respect to math). Kuhfeld (2019) also finds that the slide is larger in higher grades than in lower grades, and that performance gaps between minority and nonminority students did not increase, but gaps between students in high-poverty versus low-poverty schools increased significantly but by a small amount (at most, students in high-poverty schools lost one week of learning). The two studies (Atteberry and McEachin 2020 and Kuhfeld 2019) use the NWEA’s MAP Growth reading and math assessments. von Hippel, Workman, and Downey (2018) estimate that during the summer, performance gaps by socioeconomic status slightly increase for children in their first years in school. Our own exploratory analysis of the ECLS-K 2010–2011 data coincides with finding most students experience gains during the summers (both in math and reading), and that the performance gaps widen between low- and high-income children (using household income as a proxy for socioeconomic status). See also Quinn et al. 2016.

8. Definitions of chronic absenteeism vary by study, school district, etc. They typically are based on the number of days or a share of days missed over an entire school year, and they are only available on a yearly basis. For example, the U.S. Department of Education (2016) defines chronically absent students as those who “miss at least 15 days of school in a year.” Elsewhere, chronic absenteeism is frequently defined as missing 10% or more of the total number of days the student is enrolled in school or missing a month or more of school in the previous year (Ehrlich et al. 2013; Balfanz and Byrnes 2012).

9. Some examples are J-PAL 2017, Jordan 2019, and Balu 2019.

10. This 1.5 million figure is of course not completely illustrative today because overall enrollment numbers are expected to have grown since 2010. As a related reference, the National Center for Education Statistics estimates that there were 656 virtual schools in the U.S. in 2017–2018, enrolling about 279,000 students (0.55 percent of total enrollment) (NCES 2019b).

11. The literature on use of devices for education covers a lot of ground: findings tend to be a function of the type of technology/device used, the intensity, the developmental period/age, etc. (Crone and Konijn 2018; Walsh et al. 2018, see a summary in García 2018). To illustrate a few of these associations, researchers have found that time spent using a mobile phone and watching TV and sending text messages is correlated with lower achievement, slower reading times, and more intuitive but less analytic thinking, and it is also correlated with a faster but less accurate performance in a test of selective attention capacity and skills, as well as in processing-speed ability (Evans-Schmidt and Vandewater 2008; Lepp, Barkley, and Karpinski 2014; Fox, Rosen, and Crawford 2009; Barr et al. 2015; Abramson et al. 2009). Video-gaming can positively influence visual attention and spatial skills (attention capacity, quicker attention deployment, and faster processing,  according to Evans-Schmidt and Vandewater 2008). More frequent use of social media is negatively correlated with grade point averages (GPA), academic performance, and hours per week spent studying (Junco 2012; Karpinski et al. 2012; Kirschner and Karpinski 2010). Texting, using Facebook (and accessing Facebook while studying), and conducting internet searches unrelated to academic activity concurrent with homework completion all negatively correlate with GPA (Junco and Cotten 2012; Rosen, Carrier, and Cheever 2013; Wilmer, Sherman and Chein 2017). Media use (including social media) positively correlates with social and emotional learning (SEL) development, relationships with peers, and engagement, but also with addiction, bullying, mood and self-esteem problems, and time not sleeping/exercising/studying, some due to the trade-offs between time spent on some of these activities (Crone and Konijn 2018; Lemola et al. 2015; American Academy of Pediatrics 2011). The evidence also points out that if the content watched is high-quality educational programming, and does not displace other cognitively enriching experiences, screen time is positively correlated with achievement, engagement, and attitudes toward learning (Evans-Schmidt and Vandewater 2008). Concerns with excessive screen time have been well covered in the media during the months of the pandemic. See for example Kamenetz 2020a; Cheng and Wilkinson 2020.

12. Some information for households with children during the pandemic has been released by the U.S. Census Bureau through the Household Pulse Survey Tables for a target population of adults 18 years and older. See U.S. Census Bureau 2020a.

13. They say: “These students’ learning and persistence outcomes are worse when they take online courses than they would have been had these same students taken in-person courses.” See Zhao 2020 for some discussion of the challenges around online learning. NCES has used this period to build a repository of this research, which is discussed in Soldner 2020.

14. One in three online charter schools reported that all of their courses were self-paced. On average, online charter schools provide less simultaneous learning and teaching in a week than conventional schools would have in a day and less one-on-one instruction, with larger student-to-teacher ratios. Principals in these schools reported that the greatest challenge was student engagement (a challenge cited almost three times as often as any other issue) (Gill et al. 2015). Based on national data, across all tested students in online charters, the typical annual academic losses are -0.25 SD for math and -0.10 SD for reading (Woodworth et al. 2015). See Bueno 2020 for a more updated study of full-time virtual school attendance in Georgia, which shows negative effects ranging from -0.1 to -0.4 SD on performance.

15. This share has been relatively stable since 2007.

16. Subjects tested include reading, language l, mathematics (with computation), science, social studies, core (with computation), and composite (with computation).

17. As researchers note, the evidence is limited by the inability to use experimental or even quasi-experimental methods, precluding them from drawing conclusions as to causality (Belfield 2004; Cheng and Donnelly 2019; Lubienski, Pukett, and Brewer 2013). Belfield (2004) explains the three empirical issues that arise when comparing outcomes from home schooling against public schooling: 1) the common concern over the endogeneity of school choice, that is different types of families choose the type of school that their children attend, and little can be inferred about the impacts of schools for students who do not attend them; 2) the need to distinguish the absolute performance of home-schoolers from the treatment effect of home schooling—“Given the above-median resources of many home-schooling families, academic performance should be high even if home schooling itself is not differentially effective. Full controls for family background are needed, however, to identify a treatment effect”; 3) “home-schoolers can often choose which tests to take and when to take them (and have parents administer them), introducing other biases.”

18. Bacher-Hicks, Goodman, and Mulhern (2020) examine the search for online learning platforms used by schools and supplemental resources on Google. They find that the search intensity had roughly doubled relative to baseline. (They also find that the intensity rose twice as much in areas with above-median SES as in areas with below-median SES, where SES is measures by household income, parental education, and computer and internet access.

19. This lack of time for planning has in a way continued during the summer. As the news reports have broadly shown, many schools were going to reopen but they had to cancel at the last minute, which probably meant that the plans in place were no longer aligned with students’ and teachers’ needs. In other cases, the uncertainty about resources available (as discussed later in the report) led to a squandered opportunity to plan accordingly.

20. The authors point to the nine factors that determine the quality of online teaching and learning, including modality, pacing, student-instructor ratio, pedagogy (type), role of online assessments, students’ online roles, instructors’ online roles, online communication synchrony, and source of feedback. While all may not apply as strongly in K–12 education, the range of considerations highlights the challenges public school teachers will face in attempting to make remote instruction effective.

21. More broadly, these aspects about online instruction also touch upon the relevance of teacher professional development, the importance of establishing learning communities for teachers, and teachers’ access to a sound system of supports (Darling-Hammond et al. 2017; Kraft, Blazar, and Hogan 2018; García and Weiss 2019). Among other advantages, learning communities allow teachers to acquire new skills, update their knowledge, and strengthen their practice and effectiveness in the classroom, all critically important factors for education quality and also for the stability of the teaching workforce (García and Weiss 2019).

22. As we explained in our study, the professional development module that delivered data for the 2011–2012 SASS is rotating and was not included in the most recent data set available when we were conducting our study (2015–2016), but it will be in the next cycle, 2017–2018.

23. Teachers also reported having very little input on which activities to undertake for their professional development. Only 11.1 percent of teachers have a great deal of influence determining the content of in-service professional development programs. As we noted in García and Weiss 2019, this disregard for teachers’ input is quite troubling, given national and international surveys and testimonies showing that teachers want to play a more direct role in selecting the types and content of professional development opportunities offered to them (see Bill & Melinda Gates Foundation 2014; Loewus 2019; OECD 2019; Kirk 2019; Schwartz 2019).

24. For example, in Washington, D.C., the school district has indicated attendance is compulsory for students ages 5–17. Schools will use daily attendance as an indicator of student engagement in learning together with information on completing assignments and participation in live classes (District of Columbia Office of the Mayor 2020).

25. This sharply academic focus narrowed with the 2001 passage of the federal No Child Left Behind Act, which replaced the earlier version of the Elementary and Secondary Education Act (ESEA). The 2015 passage of the Every Student Succeeds Act attempted to dial back that pressure (see CASEL 2020; Kostyo, Cardichon, and Darling-Hammond 2018). Useful references on these issues and some others discussed below are Bloom 1964; Borghans et al. 2008; Duckworth and Yeager 2015; Levin 2012; Jones et al. 2016; Jones et al. 2019; Shonkoff and Phillips 2000; Lippman et al. 2015; Petway, Brenneman, and Kyllonen 2016; UNESCO’s Incheon Declaration for Education 2030 (UNESCO et al. 2016); and our own work on these issues: García 2014; García and Weiss 2016.

26. For those interested in this approach, Tirivayi et al. (2020) offer a comprehensive examination of past public policy responses to emergency crises.

27. Technically, this is known as lack of external validity. This research documents that approximately 50 million primary- and lower-secondary-age children are out of school in conflict-affected countries around the world (Save the Children 2013). Natural disasters, which also displace large numbers of students, are four times as prevalent today as they were in the 1980s, likely due to the growing impacts of climate change, and that number is predicted to increase exponentially in the next 20 years (Oxfam International 2007; Save the Children 2008; USAID 2014).

28. Further, research has explored the effects on the communities to which children and their families migrate (known as spillover effects from emergency migrants on the host communities), as well as some of the factors that explain them. Hurricane Maria in September 2017 caused a large influx of students from Puerto Rico to Florida’s public schools—about 12,000 students between October 2017 and May 2018. Studies found immediate negative effects on the performance outcomes of host students (students in the schools accepting new students from the disaster area) following hurricane Maria. Studies also found immediate negative effects on the performance outcomes of host students following Hurricane Katrina in September 2005, though they found zero effects on Florida’s public schools following the Haitian migrant influx after the earthquake in January 2010 and two years after it (Özek 2020; Imberman, Kugler, and Sacerdote 2012; Figlio and Özek 2019). Özek (2020) found significant adverse effects of hurricane migrants on the educational outcomes of existing students in the first year. Specifically, he found that a 5-percentage-point increase in the share of hurricane migrants reduced test scores in math and in English language arts (ELA) by an amount equivalent to one to two months of instruction, increased the likelihood of being involved in a disciplinary incident by 15–20% (of the dependent variable mean) in middle and high school, and increased the likelihood of existing students leaving their schools before the start of the 2018–2019 school year by roughly 7% (with larger increases among white and African American students). Effects were mainly concentrated among higher-performing students, especially in disadvantaged school settings.

29. Historically, there is strong agreement that in these circumstances, having access to education (versus not having access) leads “to a range of positive outcomes including child protection and well-being, economic development, peace building, and reconstruction” (Burde et al. 2017).

30. Other contingency planning strategies involve providing psychosocial programs or supplemental educational activities that protect children from harm. The strategies avoid unstructured days where traumatizing memories linger, fears thrive, and violence is always possible (Sommers 1999). Some education content, for example in refugee contexts, may be designed to mitigate conflict, and peace education programs show promise in changing attitudes and behaviors toward members of those perceived as the “other” (Burde et al. 2017). As Anderson (2020) indicates, “it is not only the mechanism and approach that is used but also the quality and methods of teaching that are critical to understand.” Different mechanisms for delivering education include radio, podcast, or television broadcasts; online programs or virtual peer learning circles; and even the provision of kits with basic materials (pencils, exercise books, erasers, etc.). Another critical element is to ensure that children have access to the instructional mechanisms used.

31. A recent publication by The Century Foundation notes “the significant variation in both per-pupil spending and student outcomes across the country” and estimates that the U.S. needs to spend an additional $150 billion to ensure that all students “achieve national average outcomes” (TCF 2020). For research about the important role that opportunity gaps and family income play in education performance, see Coleman et al. 1966; Reardon 2011; García and Weiss 2017; Putnam 2015; Rothstein 2004; and Weiss and Reville 2019.

32. Food insecurity is a different measure than poverty. The former, in the Bauer article, refers to the share of households reporting to the U.S. Census Bureau that it was sometimes or often the case that the children in the household “were not eating enough because we just couldn’t afford enough food.” But poverty rates are also an instructive measure during this crisis. Using an unlikely scenario of an unemployment rate of 30% this year due to COVD-19, Parolin and Wimer (2020) estimate that poverty rates in the United States could reach their highest levels in 50 years. Specifically, they estimate that if unemployment rates stay at 30% throughout the year, the supplemental poverty measure (SPM) rate for children would rise by more than 7 percentage points, from 13.6% to 20.9% (the SPM created by the U.S. Census Bureau is a measure of poverty that some researchers consider more accurate than the official poverty measure because it takes into account income from such benefits as food stamps and housing assistance).

33. A total of 1.5 million students surveyed in the 2017–2018 school year had experienced homelessness at some point during the last three school years (USICH 2020).

34. Even if they don’t lose their jobs, some workers and virtually all essential workers don’t have access to work remotely (following the traditional racial/SES inequities). The inability to work remotely means that keeping their jobs and thus their access to health insurance disproportionately exposes them to the virus (Gould and Shierholz 2020; Bivens and Zipperer 2020) and makes it nearly impossible for them to supervise their children and assist them in their education needs.

35. For updated information, nationally and for various subgroups, see the CDC COVID Data Tracker (CDC 2020c).

36. This is a problem both for students in dense urban areas, where normally strong hospital systems have been overwhelmed at times during the pandemic, and in rural areas, where already gutted systems have lacked the capacity to deal with the onslaught of cases. See, for example, the description of New York City’s hospitals when that city was hit hard early in the pandemic in Arnold 2020 as well as Sandoval 2020’s more recent account of a small rural hospital on the Texas–Mexico border.

37. Specifically, in our studies, poor students are students eligible for the federal free or reduced-price lunch programs under federal guidelines that deliver such meals based on family income falling below a certain threshold. Non-poor students are students who are ineligible for those programs. For a recent discussion, see Cookson 2020.

38. While 25% of superintendents reported that almost all of their students (91–100%) had internet access at home and 26% reported that almost all of their students had devices to connect to the internet at home, substantial shares of superintendents reported gaps in that access: 23% estimated that just 81–90% had access to internet and devices; 16–17% estimated that 71–80% had access to internet and devices; 11% estimated that just 61–70% had access to internet and devices; 10% said the share with access to internet and devices was 50% or less; and 14% said the share with access to internet and devices was 50% or less (Rogers and Ellerson Ng 2020).

39. As early as March, Texas waived requirements that students take its standardized state STAAR test due to the closure of schools (Swaby 2020), and Massachusetts did the same in April (Lisinski 2020). See also Brookings Institution 2020; Darling-Hammond and Kini 2020; NEPC 2020; Ravitch 2020.

40. AFT 2020d. Capstone projects are end-of-year term projects that students can complete to bring the school year to a close in lieu of statewide standardized assessments (see Weingarten 2020). For some examples of these projects, see Dickinson 2020.

41. U.S. Census Bureau (2020b). McNichol and Leachman (2020) estimate “$555 billion in shortfalls over state fiscal years 2020–2022.” Bivens (2020) reviews estimates of a revenue shortfall for state and local governments of nearly $1 trillion.

42. See Baker and DiCarlo 2020; Leachman and Figueroa 2019; Partelow, Yin, and Sargrad 2020.

43. Since March 2020, the House of Representatives and the Senate have passed four coronavirus relief packages totaling over $3 trillion. The most current proposed measures are the HEROES and HEALS Acts (Lee 2020a, b; Progressive Caucus Action Fund 2020). For a discussion on the relatively small amounts that public schools and education have received, see Jordan 2020b; Reber and Gordon 2020. See also Snell 2020.

44. An obvious lesson learned from the COVID-19 crisis is that schools and related sectors like early childhood education and child care are undervalued relative to their key contributions to the societal good. Schools are “essential to the operation of the country… It is impossible to restart the economy without the schools, they go together” and are “a critical part of the social safety net for children” (ASI 2020). Education and also health and social services are “forms of investment, not consumption; necessities, not luxuries” (Folbre 2016). Just as we have learned that many formerly invisible workers are “essential” to the daily functioning of our economy, we must treat education as the essential service it is and support it as such.

45. Blad 2020; Broadwater 2020; Calargo 2020; Ferris 2020; Ferguson 2020; Strauss 2020; Valant 2020.

46. See Tinubu Ali and Herrera 2020; Cohodes 2020.

47. One potential silver lining of the coronavirus pandemic is that it brings attention to a longstanding issue in education: the inadequate systems of professional development for teachers (see García and Weiss 2019). As practitioners, researchers, and policymakers collaborate more closely on professional development offerings that will help teachers teach during the pandemic, that model can inform a broader look at the systems of professional supports available to teachers and prompt more research on what constitutes optimal professional development—i.e., what professional development offerings need to cover, how the offerings should be delivered and where and for how long, and how teachers are connected to the opportunities. As we showed in García and Weiss 2019, teachers want these supports but too often are offered one-size-fits-all programs when there is no single optimal combination valid for all teachers at all times and in all settings. Also shown in García and Weiss 2019, enhanced professional development would play a role in keeping teachers in the classroom and attracting new professionals into teaching.

48. See for example U.S. Senate 2020 for an overview of the proposed Coronavirus Child Care and Education Relief Act.

49. See CDC 2020a, 2020b; AASA 2020; UNESCO et al. 2020; NEA 2020; AFT 2020a; National Superintendents Roundtable 2020. There are still many things that scientists and public health experts do not know about the prevalence, transmission, and long-term consequences of contracting COVID-19 among children and adolescents. Likewise, there is no universally agreed on threshold of incidence of the disease under which activities can safely resume. While these questions are beyond the scope of this report and our areas of expertise, they are critical factors weighing on the reopening of our schools. Several studies point to lower prevalence of infection among children than on average but also to the need to assess whether the incidence of the disease among children can be influenced by selective testing, how prevalence of the virus among children compares with prevalence among their parents (i.e., whether the rate of infection of parents is different from their children’s), how these have changed over time (i.e., whether the immunity lasts longer for children or for parents, etc.), etc. (Idele et al. 2020; Pollán et al. 2020; Heald-Sargent et al. 2020). The American Academy of Pediatrics (2020) is requesting that schools reopen. See Goldstein 2020b.

50. While there is no precise estimate of how much following these guidelines would cost, the School Superintendents Association estimates that the average school district will need an additional $1.78 million to meet the COVID-19-related expenses of reopening schools (AASA 2020). The National Academy of Sciences estimates the cost of health-related supplies at $1.8 million for a school district serving 3,200 students (National Academies of Sciences, Engineering, and Medicine 2020). The Council of Chief State School Officers explains that the costs associated with opening schools safely under appropriate health and safety protocols would add up to about $30 billion across all schools (CCSSO 2020). The American Federation of Teachers culls from a number of sources to estimate that a total of $116.5 billion is needed for all measures, $35 billion of which would be needed for additional instructional staff to support adequate social distancing (AFT 2020b, 2020c). See also DiNapoli Jr. 2020 and Berman 2020. The cost of reopening schools is an unsettled issue.

51. See ASI 2020; CPCC, The Education Trust, NEA 2020; Duflo 2020; Brookings Institution 2020.

52. See Gordon 2013; RESEARCHED 2020.

53. AFT 2020d; Weingarten 2020; Dickinson 2020.

54. See García and Weiss 2020; Will 2020; Page 2020; Hamilton, Kaufman, and Diliberti 2020; NIRS 2020. For early retirements of teachers and principals, see Will 2020 and Page 2020. For challenges imposed by remote instruction, see Greif Green and Bettini 2020; Prothero 2020. In terms of recessions, public education job losses following the Great Recession exceeded 316,000 between September 2008 and September 2011 (BLS 2020). The job losses in April 2020 alone were already greater than in all of the Great Recession: 468,800 jobs were lost just a month after the pandemic started (Gould 2020b; see BLS 2020 for a still deeper decrease in May and a slight recovery in June and July). An estimate of the consequences of a 15% reduction in state education funding says that it could lead to the loss of more than 300,000 teaching positions (or 8.4%; see Griffith 2020).

55. See Darling-Hammond et al. 2020; Shonkoff and Phillips 2000; García and Weiss 2016; Walker, Tim 2020; Weiss and Reville 2019; Zhao 2020; Clark et al. 2020; Goldstein 2020a.

56. See Mishel and Rothstein 2003 and Schanzenbach 2020 for a recent review of the influence of class size on achievement. Note that this literature was not reviewed in the literature review section of this report because class size has generally not been a feature of the pandemic. However, in the literature, smaller classes are an implicit recommendation from various subfields. For evidence on summer programs, see McCombs et al. 2019. For evidence on tutoring effectiveness, see Nickow, Oreopoulos, and Quan 2020. On personalized learning, see Kim 2019.

57. Ferguson et al. 2020; García 2020; Hamilton, Kaufman, and Diliberti 2020.

58. Oakes, Maier, and Daniel 2017; Gonzalez 2018; Weiss and Reville 2019; Darling-Hammond et al. 2020; Starr 2020.

59. Darling-Hammond et al. (2020) discuss this framework as informed by evidence from the science of learning and development. See the different principles of practice in their Figure 1.

60. Weiss and Reville 2019; Shonkoff and Williams 2020.

61. EPI’s series of reports on the teacher shortage documents the factors that lead teachers to quit (and likely discourage people from entering the profession). See Economic Policy Institute 2020. See Allegretto and Mishel 2019 for estimates of the teacher pay penalty (how much less teachers earn in wages and benefits than comparable college-educated workers in other professions).

62. See García 2015 and García and Weiss 2017, among others.

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• 8.4 Annotated Student Sample: "U.S. Response to COVID-19" by Trevor Garcia
• 1 Unit Introduction

Introduction

• 1.1 "Reading" to Understand and Respond
• 1.2 Social Media Trailblazer: Selena Gomez
• 1.3 Glance at Critical Response: Rhetoric and Critical Thinking
• 1.4 Annotated Student Sample: Social Media Post and Responses on Voter Suppression
• 1.5 Writing Process: Thinking Critically About a “Text”
• 1.6 Evaluation: Intention vs. Execution
• 1.7 Spotlight on … Academia
• 1.8 Portfolio: Tracing Writing Development
• Further Reading
• Works Cited
• 2.1 Seeds of Self
• 2.2 Identity Trailblazer: Cathy Park Hong
• 2.3 Glance at the Issues: Oppression and Reclamation
• 2.4 Annotated Sample Reading from The Souls of Black Folk by W. E. B. Du Bois
• 2.5 Writing Process: Thinking Critically about How Identity Is Constructed Through Writing
• 2.6 Evaluation: Antiracism and Inclusivity
• 2.7 Spotlight on … Variations of English
• 2.8 Portfolio: Decolonizing Self
• 3.1 Identity and Expression
• 3.2 Literacy Narrative Trailblazer: Tara Westover
• 3.3 Glance at Genre: The Literacy Narrative
• 3.4 Annotated Sample Reading: from Narrative of the Life of Frederick Douglass by Frederick Douglass
• 3.5 Writing Process: Tracing the Beginnings of Literacy
• 3.6 Editing Focus: Sentence Structure
• 3.7 Evaluation: Self-Evaluating
• 3.8 Spotlight on … The Digital Archive of Literacy Narratives (DALN)
• 3.9 Portfolio: A Literacy Artifact
• Works Consulted
• 2 Unit Introduction
• 4.1 Exploring the Past to Understand the Present
• 4.2 Memoir Trailblazer: Ta-Nehisi Coates
• 4.3 Glance at Genre: Conflict, Detail, and Revelation
• 4.4 Annotated Sample Reading: from Life on the Mississippi by Mark Twain
• 4.5 Writing Process: Making the Personal Public
• 4.6 Editing Focus: More on Characterization and Point of View
• 4.7 Evaluation: Structure and Organization
• 4.8 Spotlight on … Multilingual Writers
• 4.9 Portfolio: Filtered Memories
• 5.1 Profiles as Inspiration
• 5.2 Profile Trailblazer: Veronica Chambers
• 5.3 Glance at Genre: Subject, Angle, Background, and Description
• 5.4 Annotated Sample Reading: “Remembering John Lewis” by Carla D. Hayden
• 5.5 Writing Process: Focusing on the Angle of Your Subject
• 5.6 Editing Focus: Verb Tense Consistency
• 5.7 Evaluation: Text as Personal Introduction
• 5.8 Spotlight on … Profiling a Cultural Artifact
• 5.9 Portfolio: Subject as a Reflection of Self
• 6.1 Proposing Change: Thinking Critically About Problems and Solutions
• 6.2 Proposal Trailblazer: Atul Gawande
• 6.3 Glance at Genre: Features of Proposals
• 6.4 Annotated Student Sample: “Slowing Climate Change” by Shawn Krukowski
• 6.5 Writing Process: Creating a Proposal
• 6.6 Editing Focus: Subject-Verb Agreement
• 6.7 Evaluation: Conventions, Clarity, and Coherence
• 6.8 Spotlight on … Technical Writing as a Career
• 6.9 Portfolio: Reflecting on Problems and Solutions
• 7.1 Thumbs Up or Down?
• 7.2 Review Trailblazer: Michiko Kakutani
• 7.3 Glance at Genre: Criteria, Evidence, Evaluation
• 7.4 Annotated Student Sample: "Black Representation in Film" by Caelia Marshall
• 7.5 Writing Process: Thinking Critically About Entertainment
• 7.6 Editing Focus: Quotations
• 7.7 Evaluation: Effect on Audience
• 7.8 Spotlight on … Language and Culture
• 7.9 Portfolio: What the Arts Say About You
• 8.1 Information and Critical Thinking
• 8.2 Analytical Report Trailblazer: Barbara Ehrenreich
• 8.3 Glance at Genre: Informal and Formal Analytical Reports
• 8.5 Writing Process: Creating an Analytical Report
• 8.6 Editing Focus: Commas with Nonessential and Essential Information
• 8.7 Evaluation: Reviewing the Final Draft
• 8.8 Spotlight on … Discipline-Specific and Technical Language
• 8.9 Portfolio: Evidence and Objectivity
• 9.1 Breaking the Whole into Its Parts
• 9.2 Rhetorical Analysis Trailblazer: Jamil Smith
• 9.3 Glance at Genre: Rhetorical Strategies
• 9.4 Annotated Student Sample: “Rhetorical Analysis: Evicted by Matthew Desmond” by Eliana Evans
• 9.5 Writing Process: Thinking Critically about Rhetoric
• 9.6 Editing Focus: Mixed Sentence Constructions
• 9.7 Evaluation: Rhetorical Analysis
• 9.8 Spotlight on … Business and Law
• 9.9 Portfolio: How Thinking Critically about Rhetoric Affects Intellectual Growth
• 10.1 Making a Case: Defining a Position Argument
• 10.2 Position Argument Trailblazer: Charles Blow
• 10.3 Glance at Genre: Thesis, Reasoning, and Evidence
• 10.4 Annotated Sample Reading: "Remarks at the University of Michigan" by Lyndon B. Johnson
• 10.5 Writing Process: Creating a Position Argument
• 10.6 Editing Focus: Paragraphs and Transitions
• 10.7 Evaluation: Varied Appeals
• 10.8 Spotlight on … Citation
• 10.9 Portfolio: Growth in the Development of Argument
• 11.1 Developing Your Sense of Logic
• 11.2 Reasoning Trailblazer: Paul D. N. Hebert
• 11.3 Glance at Genre: Reasoning Strategies and Signal Words
• 11.4 Annotated Sample Reading: from Book VII of The Republic by Plato
• 11.5 Writing Process: Reasoning Supported by Evidence
• 12.1 Introducing Research and Research Evidence
• 12.2 Argumentative Research Trailblazer: Samin Nosrat
• 12.3 Glance at Genre: Introducing Research as Evidence
• 12.4 Annotated Student Sample: "Healthy Diets from Sustainable Sources Can Save the Earth" by Lily Tran
• 12.5 Writing Process: Integrating Research
• 12.6 Editing Focus: Integrating Sources and Quotations
• 12.7 Evaluation: Effectiveness of Research Paper
• 12.8 Spotlight on … Bias in Language and Research
• 12.9 Portfolio: Why Facts Matter in Research Argumentation
• 13.1 The Research Process: Where to Look for Existing Sources
• 13.2 The Research Process: How to Create Sources
• 13.3 Glance at the Research Process: Key Skills
• 13.4 Annotated Student Sample: Research Log
• 13.5 Research Process: Making Notes, Synthesizing Information, and Keeping a Research Log
• 13.6 Spotlight on … Ethical Research
• 14.1 Compiling Sources for an Annotated Bibliography
• 14.2 Glance at Form: Citation Style, Purpose, and Formatting
• 14.3 Annotated Student Sample: “Healthy Diets from Sustainable Sources Can Save the Earth” by Lily Tran
• 14.4 Writing Process: Informing and Analyzing
• 15.1 Tracing a Broad Issue in the Individual
• 15.2 Case Study Trailblazer: Vilayanur S. Ramachandran
• 15.3 Glance at Genre: Observation, Description, and Analysis
• 15.4 Annotated Sample Reading: Case Study on Louis Victor "Tan" Leborgne
• 15.5 Writing Process: Thinking Critically About How People and Language Interact
• 15.6 Editing Focus: Words Often Confused
• 15.7 Evaluation: Presentation and Analysis of Case Study
• 15.8 Spotlight on … Applied Linguistics
• 15.9 Portfolio: Your Own Uses of Language
• 3 Unit Introduction
• 16.1 An Author’s Choices: What Text Says and How It Says It
• 16.2 Textual Analysis Trailblazer: bell hooks
• 16.3 Glance at Genre: Print or Textual Analysis
• 16.4 Annotated Student Sample: "Artists at Work" by Gwyn Garrison
• 16.5 Writing Process: Thinking Critically About Text
• 16.6 Editing Focus: Literary Works Live in the Present
• 16.7 Evaluation: Self-Directed Assessment
• 16.8 Spotlight on … Humanities
• 16.9 Portfolio: The Academic and the Personal
• 17.1 “Reading” Images
• 17.2 Image Trailblazer: Sara Ludy
• 17.3 Glance at Genre: Relationship Between Image and Rhetoric
• 17.4 Annotated Student Sample: “Hints of the Homoerotic” by Leo Davis
• 17.5 Writing Process: Thinking Critically and Writing Persuasively About Images
• 17.6 Editing Focus: Descriptive Diction
• 17.7 Evaluation: Relationship Between Analysis and Image
• 17.8 Spotlight on … Video and Film
• 17.9 Portfolio: Interplay Between Text and Image
• 18.1 Mixing Genres and Modes
• 18.2 Multimodal Trailblazer: Torika Bolatagici
• 18.3 Glance at Genre: Genre, Audience, Purpose, Organization
• 18.4 Annotated Sample Reading: “Celebrating a Win-Win” by Alexandra Dapolito Dunn
• 18.5 Writing Process: Create a Multimodal Advocacy Project
• 18.6 Evaluation: Transitions
• 18.7 Spotlight on . . . Technology
• 18.8 Portfolio: Multimodalism
• 19.1 Writing, Speaking, and Activism
• 19.2 Podcast Trailblazer: Alice Wong
• 19.3 Glance at Genre: Language Performance and Visuals
• 19.4 Annotated Student Sample: “Are New DOT Regulations Discriminatory?” by Zain A. Kumar
• 19.5 Writing Process: Writing to Speak
• 19.6 Evaluation: Bridging Writing and Speaking
• 19.7 Spotlight on … Delivery/Public Speaking
• 19.8 Portfolio: Everyday Rhetoric, Rhetoric Every Day
• 20.1 Thinking Critically about Your Semester
• 20.2 Reflection Trailblazer: Sandra Cisneros
• 20.3 Glance at Genre: Purpose and Structure
• 20.4 Annotated Sample Reading: “Don’t Expect Congrats” by Dale Trumbore
• 20.5 Writing Process: Looking Back, Looking Forward
• 20.6 Editing Focus: Pronouns
• 20.7 Evaluation: Evaluating Self-Reflection
• 20.8 Spotlight on … Pronouns in Context

Learning Outcomes

By the end of this section, you will be able to:

• Identify the genre conventions of an informal analytical report.
• Analyze the organizational structure of a report and how writers develop ideas.
• Recognize how writers use evidence and objectivity to build credibility.
• Identify sources of evidence within a text and in source citations.

The analytical report that follows was written by a student, Trevor Garcia, for a first-year composition course. Trevor’s assignment was to research and analyze a contemporary issue in terms of its causes or effects. He chose to analyze the causes behind the large numbers of COVID-19 infections and deaths in the United States in 2020. The report is structured as an essay, and its format is informal.

Living by Their Own Words

Successes and failures.

student sample text With more than 83 million cases and 1.8 million deaths at the end of 2020, COVID-19 has turned the world upside down. By the end of 2020, the United States led the world in the number of cases, at more than 20 million infections and nearly 350,000 deaths. In comparison, the second-highest number of cases was in India, which at the end of 2020 had less than half the number of COVID-19 cases despite having a population four times greater than the U.S. (“COVID-19 Coronavirus Pandemic,” 2021). How did the United States come to have the world’s worst record in this pandemic? An examination of the U.S. response shows that a reduction of experts in key positions and programs, inaction that led to equipment shortages, and inconsistent policies were three major causes of the spread of the virus and the resulting deaths. end student sample text

annotated text Introduction. Informal reports follow essay structure and open with an overview. end annotated text

annotated text Statistics as Evidence. The writer gives statistics about infection rates and numbers of deaths; a comparison provides context. end annotated text

annotated text Source Citation in APA Style: No Author. A web page without a named author is cited by the title and the year. end annotated text

annotated text Thesis Statement. The rhetorical question leads to the thesis statement in the last sentence of the introduction. The thesis statement previews the organization and indicates the purpose—to analyze the causes of the U.S. response to the virus. end annotated text

Reductions in Expert Personnel and Preparedness Programs

annotated text Headings. This heading and those that follow mark sections of the report. end annotated text

annotated text Body. The three paragraphs under this heading support the first main point in the thesis statement. end annotated text

student sample text Epidemiologists and public health officials in the United States had long known that a global pandemic was possible. end student sample text

annotated text Topic Sentence. The paragraph opens with a sentence stating the topic. The rest of this paragraph and the two that follow develop the topic chronologically. end annotated text

student sample text In 2016, the National Security Council (NSC) published Playbook for Early Response to High-Consequence Emerging Infectious Disease Threats and Biological Incidents , a 69-page document on responding to diseases spreading within and outside of the United States. On January 13, 2017, the joint transition teams of outgoing president Barack Obama and then president-elect Donald Trump performed a pandemic preparedness exercise based on the playbook; however, it was never adopted by the incoming administration (Goodman & Schulkin, 2020). A year later, in February 2018, the Trump administration began to cut funding for the Prevention and Public Health Fund at the Centers for Disease Control and Prevention, leaving key positions unfilled. Other individuals who were fired or resigned in 2018 were the homeland security adviser, whose portfolio included global pandemics; the director for medical and biodefense preparedness; and the top official in charge of a pandemic response. None of them were replaced, thus leaving the White House with no senior person who had experience in public health (Goodman & Schulkin, 2020). Experts voiced concerns, among them Luciana Borio, director of medical and biodefense preparedness at the NSC, who spoke at a symposium marking the centennial of the 1918 influenza pandemic in May 2018: “The threat of pandemic flu is the number one health security concern,” she said. “Are we ready to respond? I fear the answer is no” (Sun, 2018, final para.). end student sample text

annotated text Audience. The writer assumes that his readers have a strong grasp of government and agencies within the government. end annotated text

annotated text Synthesis. The paragraph synthesizes factual evidence from two sources and cites them in APA style. end annotated text

annotated text Expert Quotation as Supporting Evidence. The expert’s credentials are given, her exact words are placed in quotation marks, and the source is cited in parentheses. end annotated text

annotated text Source Citation in APA Style: No Page Numbers. Because the source of the quotation has no page numbers, the specific paragraph within the source (“final para.”; alternatively, “para. 18”) is provided in the parenthetical citation. end annotated text

student sample text Cuts continued in 2019, among them a maintenance contract for ventilators in the federal emergency supply and PREDICT, a U.S. agency for international development designed to identify and prevent pandemics (Goodman & Schulkin, 2020). In July 2019, the White House eliminated the position of an American public health official in Beijing, China, who was working with China’s disease control agency to help detect and contain infectious diseases. The first case of COVID-19 emerged in China four months later, on November 17, 2019. end student sample text

annotated text Development of First Main Point. This paragraph continues the chronological development of the first point, using a transitional sentence and evidence to discuss the year 2019. end annotated text

student sample text After the first U.S. coronavirus case was confirmed in 2020, the secretary of the Department of Health and Human Services (HHS) was named to lead a task force on a response, but after several months, he was replaced when then vice president Mike Pence was officially charged with leading the White House Coronavirus Task Force (Ballhaus & Armour, 2020). Experts who remained, including Dr. Deborah Birx and Dr. Anthony Fauci of the National Institutes of Health, were sidelined. Turnover of personnel in related government departments and agencies continued throughout 2020, leaving the country without experts in key positions to lead the pandemic response. end student sample text

annotated text Development of First Main Point. This paragraph continues the chronological development of the first point, using a transitional sentence and evidence to discuss the start of the pandemic in 2020. end annotated text

Inaction and Equipment Shortages

annotated text Body. The three paragraphs under this heading support the second main point in the thesis statement. end annotated text

student sample text In January and February of 2020, the president’s daily brief included more than a dozen detailed warnings, based on wire intercepts, computer intercepts, and satellite images by the U.S. intelligence community (Miller & Nakashima, 2020). Although senior officials began to assemble a task force, no direct action was taken until mid-March. end student sample text

annotated text Topic Sentences. The paragraph opens with two sentences stating the topic that is developed in the following paragraphs. end annotated text

student sample text The stockpile of medical equipment and personal protective equipment was dangerously low before the pandemic began. Although the federal government had paid $9.8 million to manufacturers in 2018 and 2019 to develop and produce protective masks, by April 2020 the government had not yet received a single mask (Swaine, 2020). Despite the low stockpile, a request by the head of the Food and Drug Administration (FDA) in early 2020 to begin contacting companies about possible shortages of necessary medical equipment, including personal protective equipment, was denied. This decision was made to avoid alarming the industry and the public and to avoid giving the impression that the administration was not prepared for the pandemic (Ballhaus & Armour, 2020). end student sample text

annotated text Topic Sentence. The paragraph opens with a sentence stating the topic that is developed in the paragraph. end annotated text

annotated text Objective Stance. The writer presents evidence (facts, statistics, and examples) in mostly neutral, unemotional language, which builds trustworthiness, or ethos , with readers. end annotated text

annotated text Synthesis. The paragraph synthesizes factual evidence from two sources. end annotated text

student sample text When former President Trump declared a national emergency on March 13, federal agencies began placing bulk orders for masks and other medical equipment. These orders led to critical shortages throughout the nation. In addition, states were instructed to acquire their own equipment and found themselves bidding against each other for the limited supplies available, leading one head of a coronavirus team composed of consulting and private equity firms to remark that “the federal stockpile was . . . supposed to be our stockpile. It’s not supposed to be states’ stockpiles that they then use” (Goodman & Schulkin, 2020, April 2, 2020). end student sample text

Policy Decisions

annotated text Body. The paragraph under this heading addresses the third main point in the thesis statement. end annotated text

student sample text Policy decisions, too, hampered the U.S. response to the pandemic. end student sample text

student sample text Although the HHS and NSC recommended stay-at-home directives on February 14, directives and guidelines for social distancing were not announced until March 16, and guidelines for mask wearing were inconsistent and contradictory (Goodman & Schulkin, 2020). Implementing the recommendations was left to the discretion of state governors, resulting in uneven stay-at-home orders, business closures, school closures, and mask mandates from state to state. The lack of a consistent message from the federal government not only delegated responsibility to state and local governments but also encouraged individuals to make their own choices, further hampering containment efforts. Seeing government officials and politicians without masks, for example, led many people to conclude that masks were unnecessary. Seeing large groups of people standing together at political rallies led people to ignore social distancing in their own lives. end student sample text

annotated text Synthesis. The paragraph synthesizes factual evidence from a source and examples drawn from the writer’s observation. end annotated text

student sample text Although the first cases of COVID-19 were detected in the United States in January, genetic researchers later determined that the viral strain responsible for sustained transmission of the disease did not enter the country until around February 13 (Branswell, 2020), providing further evidence that the failed U.S. response to the pandemic could have been prevented. Cuts to public health staff reduced the number of experts in leadership positions. Inaction in the early months of the pandemic led to critical shortages of medical equipment and supplies. Mixed messages and inconsistent policies undermined efforts to control and contain the disease. Unfortunately, the response to the disease in 2020 cannot be changed, but 2021 looks brighter. Most people who want the vaccine—nonexistent at the beginning of the pandemic and unavailable until recently—will have received it by the end of 2021. Americans will have experienced two years of living with the coronavirus, and everyone will have been affected in some way. end student sample text

annotated text Conclusion. The report concludes with a restatement of the main points given in the thesis and points to the future. end annotated text

Ballhaus, R., & Armour, S. (2020, April 22). Health chief’s early missteps set back coronavirus response. Wall Street Journal . https://www.wsj.com/articles/health-chiefs-early-missteps-set-back-coronavirus-response-11587570514

Branswell, H. (2020, May 26). New research rewrites history of when COVID-19 took off in the U.S.—and points to missed chances to stop it . STAT. https://www.statnews.com/2020/05/26/new-research-rewrites-history-of-when-covid-19-arrived-in-u-s-and-points-to-missed-chances-to-stop-it/

COVID-19 coronavirus pandemic . (2021, January 13). Worldometer. https://www.worldometers.info/coronavirus/#countries

Goodman, R., & Schulkin, D. (2020, November 3). Timeline of the coronavirus pandemic and U.S. response . Just Security. https://www.justsecurity.org/69650/timeline-of-the-coronavirus-pandemic-and-u-s-response/

Miller, G., & Nakashima, E. (2020, April 27). President’s intelligence briefing book repeatedly cited virus threat. Washington Post . https://www.washingtonpost.com/national-security/presidents-intelligence-briefing-book-repeatedly-cited-virus-threat/2020/04/27/ca66949a-8885-11ea-ac8a-fe9b8088e101_story.html

Sun, L. H. (2018, May 10). Top White House official in charge of pandemic response exits abruptly. Washington Post . https://www.washingtonpost.com/news/to-your-health/wp/2018/05/10/top-white-house-official-in-charge-of-pandemic-response-exits-abruptly/

Swaine, J. (2020, April 3). Federal government spent millions to ramp up mask readiness, but that isn’t helping now. Washington Post . https://www.washingtonpost.com/investigations/federal-government-spent-millions-to-ramp-up-mask-readiness-but-that-isnt-helping-now/2020/04/03/d62dda5c-74fa-11ea-a9bd-9f8b593300d0_story.html

annotated text References Page in APA Style. All sources cited in the text of the report, and only those sources, are listed in alphabetical order with full publication information. See the Handbook for more on APA documentation style. end annotated text

Discussion Questions

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11 Meaningful Writing Assignments Connected to the Pandemic

Writing gives students an outlet to express their feelings and connect with others during this unsettling time in their lives.

With students currently at home because of the pandemic, it’s helpful to provide learning opportunities that get them talking about what’s happening in the world with trusted adults and peers.

These ideas for home assignments build connection and help our young people process this difficult experience while developing their writing skills.

11 Writing Assignments for the Current Moment

1. Interview senior members of the community: With our older community members at higher risk, hearing their stories has increasing significance. Generate interview questions with your students, and conduct a sample interview as a model.

Students can interview family members, senior members of the school staff, or others through handwritten letters, phone calls, or video chats. When students write up and share their interviews with the class, they will get a broader, more nuanced view of older generations’ experiences.

2. Folding stories: In the traditional version of this activity, one person writes a sentence or two on a piece of paper and then folds the paper so that only the last word or phrase can be seen. The next person continues the story for a few sentences before again hiding all but the last word or phrase and then passing the paper on.

To do this remotely, set up a randomized list of all of your students. The first student sends you their contribution, and you send the last phrase of that to the next name on the list. Compile all the contributions in order in a Google Doc to create a single story. Once everyone has contributed, share the whole story with the class.

The format may allow students an imaginative outlet for anxious thoughts and predictions about the future, and the result is almost guaranteed to be hilarious and inspiring to both eager and reluctant writers.

3. Dialogue journals: A journal in which a teacher and student write back and forth to each other is an ongoing communication that helps teachers build relationships with each student while they model writing and observe students’ progressing skills. Start this off by writing a first short entry for each of your students in separate Google Docs, choosing topics you already know they’re interested in and offering personal details about yourself.

You can ask each student to write something once a week—and you’ll respond to each entry, so this does entail a time commitment on your part. The benefit in relationship-building, so difficult to do in distance learning, makes this worth the work.

4. Student-to-student letters: Organize pen pals or small letter-writing groups. Ask students to write back and forth to one or more peers using provided prompts and sample questions. Teach students to consider their audience and to keep a written dialogue going over several letters as they write to different peers. Encourage students to include self-created activities in their letters to peers: They might make a crossword puzzle using the class vocabulary words, create a maze, or share a recipe or a silly joke.

5. Write to an author: A professional writer may be a great correspondent for a young fan, offering insight into key aspects of a favorite book. Follow #WriteToAnAuthor on Twitter for access to mailing addresses of authors who are standing by for letters from young readers. Provide your students with prompts, templates, samples, and feedback to support them in writing thoughtful letters.

6. Adapt a text to reflect current conditions: Lately any story we read or watch can be a painful reminder of how much is changing. Characters are dancing, hugging or shaking hands, and talking to each other in public places. Some students find it comforting to be immersed in that world, but others find these moments upsetting. Assign students the task of rewriting a scene from a story, show, or movie, considering what needs to change for it to be realistic in our current situation but still retain the original essential themes and meaning.

7. Letters to the editor: What do students think about our leaders, policies, and proposed solutions to this pandemic? Guide them through the art of writing a well-crafted letter to the editor, and post submissions on your district, school, or class website, if privacy policies permit that. Give your students guidelines that specify word count, style, and topics, just as official publications do.

8. Student-created blog: Begin by sharing strong examples of student journalism as mentor texts. Invite students to brainstorm ideas for articles and columns. Some students can assume the role of section editors—News, Features, Arts—and others can write articles, take photos, and work on the design and marketing of the website, which students can build using Edublogs .

9. “Slow looking” documentation: Shari Tishman describes “slow looking” as prolonged observation that occurs through all the senses. Students can use a variety of slow looking strategies to observe their setting and sketch or write about their observations. There are seasonal changes to observe, among other things. By practicing slow looking, students may learn to see things they never noticed before. When they share their observations with the class, everyone gains a broader perspective of how the larger environment is changing.

10. Covid-19 comics: The genre of  graphic medicine —which uses comics to explore the physical and emotional impacts of medical conditions—shows that comics can be a good way for students to explore troubling experiences. Share comics related to Covid-19  that engage with the wider implications of the pandemic, such as feeling increased isolation, processing conflicting news, and coping with social distancing or unemployment.

Invite students to explore their experiences through an intentional combination of words and pictures. Make it collaborative by having students write text for a peer’s drawings. Students can use Canva to make comics , or draw them on paper and then take photos to upload to the class learning management system.

11. Pandemic journals: A pandemic journal invites students to process their feelings and document their experience for future generations. To structure the assignment, provide prompts and templates. Suggest to students that they layer in artifacts such as news reports, a note received from a friend or neighbor, a copy of an online school schedule for a day, a snippet of an overheard conversation, or a sketch of a parent hunched over a laptop.

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Open Access

Peer-reviewed

Research Article

Student’s experiences with online teaching following COVID-19 lockdown: A mixed methods explorative study

Roles Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Faculty of Health Sciences, Department of Nursing and Health Promotion, Oslo Metropolitan University, Oslo, Norway

Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing

Roles Formal analysis, Investigation, Methodology, Writing – review & editing

Affiliation Department of Primary and Secondary Teacher Education, Faculty of Education and International Studies, Oslo Metropolitan University, Oslo, Norway

Roles Investigation, Methodology, Writing – review & editing

Roles Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing

• Kari Almendingen, 
• Marianne Sandsmark Morseth, 
• Eli Gjølstad, 
• Asgeir Brevik, 
• Christine Tørris

• Published: August 31, 2021
• https://doi.org/10.1371/journal.pone.0250378
• Reader Comments

The COVID-19 pandemic lead to a sudden shift to online teaching and restricted campus access.

To assess how university students experienced the sudden shift to online teaching after closure of campus due to the COVID-19 pandemic.

Material and methods

Students in Public Health Nutrition answered questionnaires two and 12 weeks (N = 79: response rate 20.3% and 26.6%, respectively) after the lockdown in Norway on 12 March 2020 and participated in digital focus group interviews in May 2020 (mixed methods study).

Findings and discussion

Two weeks into the lockdown, 75% of students reported that their life had become more difficult and 50% felt that learning outcomes would be harder to achieve due to the sudden shift to online education. Twelve weeks into the lockdown, the corresponding numbers were 57% and 71%, respectively. The most pressing concerns among students were a lack of social interaction, housing situations that were unfit for home office purposes, including insufficient data bandwidth, and an overall sense of reduced motivation and effort. The students collaborated well in digital groups but wanted smaller groups with students they knew rather than being randomly assigned to groups. Most students agreed that pre-recorded and streamed lectures, frequent virtual meetings and student response systems could improve learning outcomes in future digital courses. The preference for written home exams over online versions of previous on-campus exams was likely influenced by student’s familiarity with the former. The dropout rate remained unchanged compared to previous years.

The sudden shift to digital teaching was challenging for students, but it appears that they adapted quickly to the new situation. A lthough the concerns described by students in this study may only be representative for the period right after campus lockdown, the study provide the student perspective on a unique period of time in higher education.

Citation: Almendingen K, Morseth MS, Gjølstad E, Brevik A, Tørris C (2021) Student’s experiences with online teaching following COVID-19 lockdown: A mixed methods explorative study. PLoS ONE 16(8): e0250378. https://doi.org/10.1371/journal.pone.0250378

Editor: Mohammed Saqr, KTH Royal Institute of Technology, SWEDEN

Received: September 30, 2020; Accepted: April 6, 2021; Published: August 31, 2021

Copyright: © 2021 Almendingen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The Coronavirus 2019 (COVID-19) pandemic has caused extraordinary challenges in the global education sector [ 1 , 2 ]. Most countries temporarily closed educational institutions in an attempt to contain the spread of the virus and reduce infections [ 3 ]. In Norway, the move to online teaching and learning methods accelerated as a consequence of the physical closure of universities and university colleges on 12 March 2020 [ 4 ]. Education is better implemented through active, student-centered learning strategies, as opposed to traditional educator-centered pedagogies [ 5 , 6 ]. At the time of the COVID-19 outbreak, the decision to boost the use of active student-centered learning methods and digitalisation had already been made at both the governmental and institutional levels [ 7 , 8 ] because student-active learning (such as use of student response systems and flipping the classroom) increase motivation and improve learning outcomes [ 5 , 7 , 9 ]. However, the implementation of this insight was lagging behind. Traditional educator-centered pedagogies dominated higher education in Norway prior to the lockdown, and only 30% of academic teachers from higher institutions reported having any previous experience with online teaching [ 4 ]. Due to the COVID-19 lockdown, most educators had to change their approaches to most aspects of their work overnight: teaching, assessment, supervision, research, service and engagement [ 4 , 10 ].

Bachelor’s and master’s in Public Health Nutrition (PHN) represents two small-sized programmes at Oslo Metropolitan University (OsloMet). PHN is defined as ‘the application of nutrition and public health principles to design programs, systems, policies, and environments that aims to improve or maintain the optimal health of populations and targeted groups’ [ 11 , 12 ]. Traditional teaching methods dominated on both programs during winter 2020. Following the lockdown, online learning for the continuation of academic activities and the prevention of dropouts from study programmes in higher education were given the highest priority. Due to an extraordinary effort by both the administrative and academic staff, digital alternatives to the scheduled on-campus academic activities were offered to PHN students already in the first week following lockdown. The scheduled on-campus lectures were mainly offered as live-streamed plenary lectures lasting 30–45 minutes, mainly using the video conferencing tool Zoom. Throughout the spring semester educators received training in digital teaching from the institution and increasingly made use of online student response systems (such as Padlet and Mentimeter) as well as tools to facilitate digital group-work (Zoom/Microsoft Teams). Non-theoretical lectures (e.g. cooking classes), were cancelled, and face-to-face exams were re-organized into digital alternatives in order to ensure normal teaching operations. Several small tweaks were employed to minimize dropout. There was no time for coordinating the different courses with regards to the types of online teaching activities, exams and assessments. Social media, i.e Facebook, and SMS were the primary communication channels the first week after lockdown. The use of learning management systems (LMS) Canvas and digital assessment system, Inspera, remained mainly unchanged. Due to the new situation, the deadline for the submission of bachelor theses was postponed by 48 hours. In addition, bachelor students submitting their thesis where given permission to use the submission deadline for the deferred exam in August as their ordinary exam deadline. The deadline for the submission of master theses was extended by one week, but all planned master exams were completed by the end of June, including oral examinations using Zoom instead of the traditional face-to-face examinations on campus. Even though most of the new online activities where put in place with limited regard for subtle nuances of pedagogical theory, and did not allow for much student involvement, the dropout rate from PHN programs remained unchanged compared to previous years. PHN is a small-sized education with close follow up of students. However, although the students experienced a digital revolution overnight, we know little about how they experienced the situation after the university closed for on-campus activities.

Accordingly, the purpose of this study was to assess how Norwegian PHN students experienced the shift to digital teaching following campus lockdown. Students were also asked to provide feedback on what might improve the learning outcomes in future online lectures and courses.

Design and sampling

This study utilised a mixed methods cross-sectional design, where quantitative and qualitative methods complemented each other. An invitation to participate was sent out to 79 eligible students via multiple channels (Facebook, Teams, Zoom, LMS Canvas, SMS), with several reminders. The only eligibility criteria was being a student in PHN during spring 2020. All students received the quantitative survey. Due to few students eligible for each focus group interview, all who wanted to participate were interviewed/included. The invited students were in their second-year (n = 17) and third-year (n = 28) bachelor’s and first-year (n = 13) and second-year (n = 21) master’s programme at PHN in the Faculty of Health Sciences at OsloMet. The response rate was 16/79 (20.3%) and 21/79 (26.6%). Two focus group interviews were scheduled in each class (a total of 8) but only 4 interviews were conducted. The research team was heterogeneously composed of members with both pedagogical and health professional backgrounds.

Online questionnaire

To the best of our knowledge, this study was the first “corona” study at our Faculty. No suitable national or international questionnaire had been developed and /or validated by March 2020. Hence, online questionnaires for the present study were designed virtually ‘over-night’. The questions were however based on experiences from a large-scale interprofessional learning course using the blended learning approach at OsloMet [ 13 , 14 ] and specific experiences that academic staff in Norway reported during the first week of teaching during the lockdown [ 4 ]. The questionnaires were based on an anonymous self-administrated web survey ‘Nettskjema’ [ 15 ]. ‘Nettskjema’ is a Norwegian tool for designing and conducting online surveys with features that are customised for research purposes. It is easy to use, and the respondents can submit answers from a browser on a computer, mobile phone or tablet. During the first week after lockdown, the questionnaire was sent out to university colleagues and head of studies and revised accordingly. The questionnaires were deliberately kept short because the response rate is generally low in student surveys [ 16 ]. Ideally, we should have pretested and validated the questionnaires, but this was not possible within the short-time frame after lockdown. Items were measured on a five-level ordinal scale (Likert scale 0–5). The two forms contained both numerical and open questions, permitting both quantitative and qualitative analyses. The first questionnaire was sent out to the students on 25 March 2020 (two weeks after the closure of university campus; students were asked to submit their answers during the period from 12 March until the link was closed at Easter Holiday), and the second questionnaire was sent on 3 June 2020 (12 weeks after closure; students were asked to submit their answers during the period after Easter and until the end of the spring semester). The questionnaires were distributed as web links embedded in the LMS Canvas application. Because live-streamed lectures were offered primarily through Zoom during the first weeks, students were not asked about interactive digital teaching and tools in the first questionnaire. At the end of both questionnaires, the students were asked what they believed could improve the learning experience in future online education. The qualitative part consisted of text answers to open questions from the two electronic questionnaires.

Digital focus group interview

To capture meaningful insights into the participants experiences, we conducted digital focus group interviews [ 17 ], aiming to conduct one digital focus group interview in each class. PHN is a small sized education, and the teachers know all the students. The focus group interviews were therefore performed by two external independent researchers (EG and CT) who are not directly involved in the PHN education and had no prior knowledge to the students. The two interviewers (moderators) were middle-aged female teachers working in the university, and both have significant experience in digitalizing education. They were presented to the participants as researchers from the university. The report of this study was guided by the consolidated criteria for reporting qualitative research (COREQ). The interviews were conducted via the video conferencing system Zoom during May 2020, following internal guidelines [ 18 ]. In the focus group interviews, the participants reflected on their own experiences, and the moderator guided the discussion using a semi-structured interview guide. This guide was prepared based on the research questions. One pilot interview was conducted, which resulted in some minor changes to the interview guide. The results from the pilot interview are not included in the results. The focus group interviews lasted for approximately one hour, and five students were invited to each focus group interview. The interviews were not recorded, but the moderator took notes, ensuring that the participants remained anonymised.

Data analysis

Quantitative data are described descriptively with numbers and percentages. Apart from re-categorization of response categories, no statistical analysis was performed. Quantitative data were extracted directly from the survey system. Answers in categories 0 or 1 were categorised as ‘Disagree/slightly agree’, answers in categories 2 or 3 were categorised as ‘Somewhat agree’ and answers in categories 4 or 5 were categorised as ‘Agree’. Qualitative data were analysed using systematic text condensation (STC), inspired by Giorgi’s phenomenological approach and modified by Malterud [ 17 ]. First, the entire texts (from the interviews) were read to get an overall impression, and preliminary themes were derived from the interviews. Then, meaning units, such as sentences and words, were identified and connected with the preliminary theme to elucidate the study question. The meaning units were then coded and systemized into groups, so that meaning could be abstracted from the different code groups. Finally, the meanings of the various units were summarised. The qualitative data from the questionnaire were then extracted by the moderators, and the words and sentences were identified and abstracted. In order to ensure quality, the notes from the focus group interviews and the text answers from the questionnaires were reviewed by both moderators.

Ethical considerations

All participants gave their informed consent. The questionnaires did not include questions about personal health information or sensitive data. The quantitative data were collected through an anonymous web survey using ‘Nettskjema’ [ 15 ]. Internal routines at OsloMet for using Zoom in research interviews were applied [ 18 ]. In the interviews, the participants provided their written consent in the chat without their names and remained anonymous. The data protection was approved by the Norwegian Centre for Research Data (NSD, reference no. 846363), as PHN is a small-sized study programme and because Zoom was used for the digital focus group interviews.

Quantitative data

There were 16 (20.3%) and 21 (26.6%) students who answered the questionnaires two and 12 weeks after lockdown, respectively ( Table 1 ). Both samples had an even distribution of bachelor and master students.

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Among the respondents two and 12 weeks after lockdown, 7/16 students (44%) and 9/21 students (43%) reported having previous experience with online learning, respectively ( Table 1 ). After two weeks of forced online education, 8/16 students (50%) expected that their learning outcomes would be inferior with online education compared to their pre-COVID-19 education at campus. After 12 weeks, 15/ 21 students (71%) expected that their learning outcome would be lower, and, notably, none of the students expected that it would be higher. On both occasions, most students reported that studying had become more difficult compared to the time before the pandemic.

Several of the identified challenges with online education were reported by more than 50% of the students, and there was an uneven spread across categories of answers (Tables 2 and 3 ). Only one of 16 students (6%) agreed that they needed to increase their digital competence, but approximately half reported having technical challenges at home. All of the students agreed that the lack of contact with other students was a challenge. However, after 12 weeks, the lack of contact with academic staff seemed to pose less of a challenge.

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After 12 weeks, 20/21 students (95%) agreed that their motivation and effort had been reduced. At the same time, all students wanted to return to campus. Only 5/21 (24%) reported that their learning outcomes had not deteriorated.

Suggestions for how to increase learning outcome in future digital courses

Two weeks after lockdown, most students answered that the use of different components of online education would improve the learning outcomes in a future online course ( Table 4 ). Regarding participation in digital group work, there was a nearly even spread across the different categories of answers. Finally, participants preferred written home exams and feedback over the digital options suggested ( Table 5 ).

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After 12 weeks of (forced) online teaching, more ambivalence toward the use of digital learning tools could be detected ( Table 6 ). However, the proportion of students who agreed that digital group work would increase the learning outcomes seemed unchanged (around 1/3 of both samples). In line with the findings obtained only two weeks after lockdown, written submissions and feedback seemed to be preferable to digital exam options ( Table 7 ).

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After 12 weeks, 16/21 students (76%) agreed that social interaction plays a role in learning outcomes and well-being ( Table 8 ), and an equal proportion agreed that it was important that everyone had their camera on during teaching.

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There were 15/21 students (71%) who agreed that their digital competence and interest in digital teaching methods had increased while 6/21 students (29%) disagreed with this statement.

Qualitative data

In total, there were four master students who participated in digital focus group interviews (on two different occasions, with three students and one student in the groups, respectively).

Digital lectures.

The students were satisfied with the teaching and reported that the lecturers were competent in arranging online teaching. The lecturers were also good at adapting to the students’ wishes regarding teaching. Lectures that were streamed live (synchronous classes) were preferred over recordings (asynchronous). One student said it was a privilege to still be able to study even though the university campus was closed due to corona and all the lectures were digital. The students expressed that it is an advantage if the lecturer has digital competence to ensure that the lecture runs smoothly without digital/technical problems, or if there is a co-host who can assist. Technical competence is also important when invitation links are sent out. It signals that the student group is well taken care of. The informants described a course co-ordinator as a person with a good overview and sense of responsibility—someone who is good at structure and order. These qualities were highlighted as important in a fully digitalised teaching program.

The students did not support compulsory attendance, as it would reduce the feeling of freedom that most students value. If learning activities were compulsory, students felt it might also present challenges in dealing with their children and part-time work. The students expressed that most of their fellow students were present in lectures that went live on Zoom. One student stated that live digital lectures were best because it was easier to ask questions. When using a flipped classroom or recordings, the questions must be written down and asked afterwards, but both options (flipped classroom and live streaming) were perceived as fine.

Interestingly, the qualitative results from the questionnaire indicated that some students found it easy to ask questions, while others thought it had become more difficult. According to one student, ‘As long as we have the opportunity to ask questions online, I think it will go just fine. I commute three hours per school day to get to and from school, so I feel I have more time to work with school now that the lecture is online’.

One of the informants thought that interaction was challenging, and it did not feel as natural to ask questions in online classes. ‘Raising your hand’ was not perceived to be as easy as in the face-to-face setting on campus, which could mean that the students did not always get answers to their questions.

The students’ indicated that recorded lectures should not be longer than one hour, as it is easy to lose focus, and one must rewind the recordings. For live online lectures, two hours was deemed fine, and they were perceived as fun to watch. However, each session of the live online lectures should not be longer than 45 minutes.

The online teaching (mainly in the form of synchronous plenum lectures originally intended as on-campus lectures) was challenging in the beginning because some students fell out of the digital rooms due to technical reasons, but it got better over time. Some students experienced poor bandwidth, which led to them not being able to turn on their camera and reduced sound quality. One student stated that poor internet quality was something he could not do anything about, but it resulted in a non-optimal learning situation. It was suggested that using a flipped classroom/recorded lectures in the first weeks after lockdown could have solved this problem.

The respondents pointed out that the use of several conference systems/channels in addition to LMS Canvas provided a poor overview and ineffective communication, and they would prefer a single learning platform. The students were unsure how to contact their teachers in the first weeks after lockdown due to the use of several platforms. Even with a single contact channel (LMS), the students found that the threshold barrier for sending questions to the teacher through email was high.

When asked what they thought about ‘black screens’ (students turning off the camera), several answered that this reduced the quality of communication between the lecturer and student. The lecturer missed affirmative nods from students, and the students also likely missed parts of the communication when the camera was turned off. In some of the lectures, all of the students were encouraged to keep the camera on, and some of the lecturers asked the students questions to initiate two-way communication. The students expressed that it was nice to see the other attending students on video. Furthermore, the participants felt that the lecturers mainly engaged the students who had their camera on. However, several students said that they turned off their cameras during the lectures because the session was being recorded. Another stated that having the camera on was particularly useful when having discussions in digital groups. The students who participated in the survey wished for more recorded lectures, indicating that their lecturers did not do this often.

One of the informants assumed that she would have turned off the camera when recording the lecture, and she thought she had not contributed much. She would have to consider whether a question was ‘stupid’ before asking it, and probably she had not asked any questions at all. She thought this was due to habit, and she indicated that one might get used to being recorded. That is, if recording had been the norm and she had become accustomed to it, it would have been easier to relate to.

All of the informants agreed that presentations with audio were useful, as the material could be repeated by rewinding to the desired location. They also reported that it sometimes took a while for the teachers to post such files, even though the students found these learning resources very useful.

They noticed an increased attendance rate among their peers in the online lectures, which they perceived as positive. The reason for the increased attendance, they believed, was that many students have to make a long trip to attend class, and the threshold for participating had become lower now that all teaching was online. This was supported by the qualitative results from the questionnaire, where a student said, ‘I commute several hours per school day to get to and from school, so I feel I have more time to work with school now that the lecture is online’.

However, one of the informants pointed out that it is important for students to be able to talk to each other when the lecturer is not present, that group activities should be arranged and that they should be provided with opportunities for voluntary meetings on campus in their spare time. One of the informants believed it to be important that the students themselves have a responsibility to address the learning environment and initiate meetings in both academic and social arenas. One felt that it was not desirable that the university was responsible for social contact between peers. It was suggested that time could be set aside, for example, after teaching, so that only students could talk together. It was expressed that in order to preserve social aspects in digital teaching and learning, the first meeting should be on campus. A mentor scheme was suggested, where former students could give tips and advice on how to function as a ‘digital student’.

Digital group work.

The students expressed that they mainly collaborated well in digital groups (breakout rooms). Communication usually worked well with both the teacher and peers in these digital rooms. Nevertheless, some students reported that group work was not effective when it was carried out in ‘breakout rooms’. The students felt that the allocated time for group work was too short for collaboration, and some of the time was spent on technical challenges. There were also some students who withdrew from the group work, which the respondents believed was because some were shy. One student said that discussions during group work paid off and that communication worked well, but it was a pity that so few students participated. Getting to know the others in the group well was also deemed to be important for the level of collaboration and professional discussions. The students did not like to be randomly assigned into groups. However, they expressed that it would be advantageous to plan for more group work in smaller groups.

Another positive effect of online teaching the students highlighted was the increased amount of written feedback from lecturers on work submitted voluntarily. The students perceived that this was offered as a compensation for shorter teaching sessions.

One of the respondents thought that it was important to socially interact with peers and missed having lunch with fellow students. Others felt that there had not been many social gatherings in the group previously, and so they did not experience the absence of fellow students as a great loss. They also pointed out that students who had met each other physically at an earlier time had a different starting point in online meetings and for online education. One student stated, ‘Getting to know new peers digitally feels weird’. Furthermore, one of the informants pointed out that most people have a general need for physical contact, and that touching and eye-to-eye contact is important.

Motivation.

Some of the students were more motivated to participate in online learning activities, yet it was perceived to require greater effort to stay motivated and ‘in the course’. Some students work alongside their studies and thus do not attend classes, and others have children who must be tended to. Some indicated that student response systems such as Mentimeter, Quizlet, Padlet, Kahoot! and the use of polls was motivating factors, but it depended on the context in which they were used. Some of the students reported that they especially liked Kahoot, but it was important that the use of such response systems was done in a structured way. They expressed that they liked the teaching programme, which consisted of an introductory video and teaching in which the basics were presented, followed by group work and finally teaching, where the teacher went more in depth. This approach made it easier to follow the teaching and to ask questions.

The students said it was good for motivation when an overview of the course content was published, as it contributed to predictability and more people participate when they know what is planned.

Nevertheless, the qualitative results from the questionnaire indicated that it was difficult to get an overview of everything that needed to be done. It could be challenging to concentrate and have self-discipline due to many distractions, which reduced the students’ motivation. Several students expressed that they felt alone in their studies, and it was difficult to feel alone with the responsibility for learning the curriculum. One student wrote that there was considerable uncertainty, which negatively affected concentration, and that the COVID-19 crises was a difficult time for everyone.

Overall, these students were satisfied with the ad hoc online teaching after the lockdown, although they experienced self-perceived reduced learning outcomes compared to the pre-pandemic situation. It appears that they adapted quickly to the new situation, but they also reported difficulties with the transition to new teaching methods. Based on both the surveys and interviews, the most pressing concerns among students were a lack of social interaction, housing situations that were unsuitable for home office purposes, including insufficient data bandwidth, and a sense of reduced motivation and effort. PHN is a small sized education which enables close contact between educators and students. The low student volume might explain why the dropout rate from the bachelor and master programs remained unchanged compared to that in previous years.

Receiving teaching, supervision, exams and assessments solely through online solutions was a new experience for these students. Apart from a 15-credit mandatory bachelor course offered as hybrid learning (7), traditional teaching methods still dominated the bachelor and master study programmes of PHN in winter 2020. Importantly, the students evaluated the ad hoc solutions offered during the chaotic spring of 2020 rather than a well-planned, high-quality online education using student-active methods [ 5 ]. Teachers switched to online teaching without any time to learn the technology, or standard quality online teaching practices [ 4 ]. They had many years of experience teaching in -person, and they had arranged their lessons and interactive elements around this mode of learning. Alternatively, they had very little experience teaching online. The students’ experiences in these online learning environments, which were thrown together at the last minute, are not necessarily indicative of students’ experiences in a quality online course based on principles from Quality Matters online education [ 19 ].

Although the students reported reduced learning outcomes after 12 weeks dominated by synchronous live-streamed lectures lasting for 30–45 minutes on Zoom, they had positive attitudes toward use of digital learning materials and tools in future online courses. For asynchronous lectures, the rule of thumb in online education is less than 10–15 minutes [ 19 ]. Although lectures of 45 minute duration is far beyond what is recommended for digital teaching [ 19 ], the students responded based on their recent experiences where many teachers, for reasons of feasibility, conducted their planned on-campus lectures digitally shortly after lockdown. Some of the students also reported that they especially liked Kahoot, however, since we wanted to keep the research questionnaire short, we did not ask more in detail for concrete digital tools. A pre-corona study from OsloMet reported that physiotherapy students’ attitudes toward a flipped classroom intervention were mainly positive, although the academic outcomes from the final exam were similar to those in previous years [ 20 ]. Further, in a recent large-scale pre-COVID-19 blended learning interprofessional course conducted a few weeks ahead of the lockdown, first-year bachelor’s students at OsloMet reported positive perceptions of the blended learning approach, using only short video clips (less than 10 minutes) [ 21 ]. Approximately 3/4 of the students in that study disagreed that virtual group discussions resulted in better learning outcomes than face-to-face group discussions. The present data do not conflict with the findings from that larger-scale study.

The students expressed in various ways that online teaching with a lack of social interaction leads to worse learning outcomes and lower levels of motivation and well-being. Concerns about lack of face-to-face contact may have been aggravated by the stressful situation, and contentment with teaching methods would likely improve if teachers had been able to integrate the appropriate elements in a fully digitalized course. Face-to-face interactions provide the foundation for social communication, the lack of which can be viewed as a critical disadvantage of online learning [ 5 ]. Face-to-face training may be particular crucial for candidates expected to have communication skills, such as nutritionists [ 11 , 12 , 22 – 24 ]. The ad hoc solutions for teaching offered during the 2020 spring term were thus not in agreement with the suggested conceptual dimensions, which allow students to expand their knowledge beyond the intended learning outcome established by the teacher: motivation and attention [ 5 ].

The students expressed concerns that are common in traditional in‐class teaching as well, and such issues should not be overlooked in online teaching [ 25 , 26 ]: insufficient pre‐class study preparation, limited participation and inadequate depth in class discussions. Quality of education lies in the knowledge, skills and expertise that are conveyed as well as in the manner in which they are communicated and learned [ 7 , 26 ]. In different ways, the students’ responses revolved around central quality aspects, such as learning objectives, content, programme design, adaptation, teaching, work methods, supervision and forms of assessment [ 7 ]. These findings are in agreement with other studies on COVID‐19 and education [ 4 , 25 , 27 ].

The students stated that they received insufficient information about the exams. This is understandable because staff initially did not know how the different exams would be digitally transformed in spring term 2020. Asked about exam preferences students said that they preferred longer written exams at home, over old campus-style exams, with short timelines, adapted to an online format. They also preferred multi-day written home exams over potential alternatives such as video or podcasts, which none of them had tried before. It should be noted that they had limited experience with digital options. Student-produced podcast and video have been used as formative assessment forms at our university [ 14 ], but to lesser extent as formative assessment forms. The preference for written home exams over digital options was thus likely influenced by student’s familiarity with the former since no exams during this time-period were in the form of podcast or video. Feedback and guidance from academic staff have been found to be key aspects of study quality, and good feedback contributes to increased motivation and improved learning outcomes (6). Exam uncertainty causes undue stress, and thus a key recommendation during the transition to online learning is to ensure that all information about exams is communicated to the students clearly and in a timely manner [ 27 ].

‘Black screens’ do not necessarily reflect individuals lack of motivation and attention or embarrassment, but they may reflect a lack of digital training among freshmen or technical issues, such as poor bandwidth. Broadband bandwidth overload issues and a lack of suitable equipment will probably not be significant problems in Norway in the future. The students suggested that both flipped classrooms and live streaming should be used in future online courses. Flipping the classroom [ 9 ] ahead of live streaming, with the possibility for the students to write down questions during the live streaming or afterward in a seminar, increases flexibility. Asynchronous tools may be utilised to support students to work at different times. We cannot overlook the possibility that new students might have needs that differ from those of senior students in terms of getting accustomed to online education. Nevertheless, our date indicates that clarification of expectations constitutes an important success criteria for online teaching, especially when it comes to group work and formative and summative assessment [ 4 , 27 ].

The closure of campus may have unknown implications for society in both the short and long term [ 28 – 30 ], including impacts on educational quality and the mental health of students and academic staff [ 31 ]. If students are unable to study effectively for some unknown reason, it will make online learning ineffective, regardless of educational quality. The situation after the lockdown in Norway was confusing, and many students lost their jobs and moved back in with their parents [ 4 ]. We did not collect person-sensitive data, and thus we know little about these students’ circumstances. The dropout rate remained nearly unchanged among these students as compared to previous years. Being a small-sized education, the staff were able to follow-up each student individually using digital videoconference tools, such as Zoom and Teams. In the future, more sustainable approaches should be developed, for example, by increasing peer-to-peer interactions and through mentoring programs [ 1 ]. Reducing dropout and increasing completion rates was a strategic goal for higher education before the lockdown [ 29 ], and we do not know the impact of the lockdown on future dropout and completion rates. The high dropout rate from Massive Open Online Courses (MOOCs) has been a major concern of researchers and educators over the years [ 32 ]. Although some universities worldwide had already started offering MOOC-based undergraduate degrees before the COVID-19 pandemic [ 32 ], most MOOCs do not lead to degrees. The online courses offered in spring 2020 after the lockdown were mandatory courses leading to degrees, and thus they were not directly comparable to the voluntary MOOCs. However, such issues are premature for consideration in the present study. OsloMet is currently participating both in the future ‘The COVID-19 Multi-Country Student Well-being Study’[ 33 ] and the ‘Corona and Campus’ study [ 34 ]. The ‘Corona and Campus’ study has secondary outcomes related to teaching satisfaction and learning outcomes, and such data will have the power to inform future decision-making [ 30 ]. However, the present data were collected shortly after the national lockdown due to the COVID-19 pandemic on aspects of digitalisation relevant to the (post)-pandemic situation.

Strengths and weaknesses of the study

This study has several strengths. The most important strength is data collection shortly after a national lockdown due to the COVID-19 pandemic. The combined use of both quantitative and qualitative approaches enabled different perspectives to be captured and adds strength to the study. The triangulation allowed us to identify aspects more accurately and helped to offset the weaknesses of each approach alone. Group dynamics in focus group interviews can help bring out nuances in the data material beyond the answers to the predefined quantitative questions in the electronic questionnaires [ 17 ]. Another strength was the research team consisting of both external moderators providing objectivity, lack of vested interest and a fresh perspective, and internal evaluators who were familiar with the education and the students. One limitation is using a questionnaire which was not pre-tested or validated. However, due to time constraints shortly after campus lockdown following the COVID-19 outbreak, it was not possible to perform pre-testing or validation of the instruments used in the present study. Many of the necessary ad hoc changes to the course plans and exams (spring semester 2020) had yet to be made and decided upon when the present study was initiated, even when the first questionnaire was sent out before Easter 2020. The candidates actual achieved learning outcomes and working skills are unknown due to limited opportunities to monitor the quality of their work [ 4 ]. We do not consider it to be relevant to repeat the study, or reuse its instruments, since the acute phase after lockdown is over. PHN is a small-sized education, and the total number of students were only 79 individuals. The stress associated with the unprecedented situation may have contributed to a low response rate. Private circumstances such as poor internet connection, children at home, and lack of an adequate home office may also have contributed to a low response rate. A low response rate is also a limitation in studies performed in a normal situation [ 16 ]. We cannot rule out selection bias in the sample. The students who volunteered for the digital focus group interviews were positive and thorough. In particular, they seemed to reflect on a more general level, not restricted to their own personal situations. However, the range in age among the study participants was representative for the age range of all PHN students, and both bachelor and master students participated in the study. Data are collected from one single university, and the results might not be representative for large sized educations. Since the study is exploratory, we had not planned the data collection in order to test hypotheses. The study seeks to provide a snapshot in time of an evolving situation. Even with some limiting factors we believe the explorative study offers value since it provides a student perspective on an unprecedented black-swan event in higher education.

Conclusions

Although they had little previous experience with online education, these students seemed to adapt quickly to the sudden shift to ad hoc online education due to the COVID-19 pandemic. The most pressing concerns among students were a lack of social interaction, a feeling of being alone in their studies, unfit housing situations for home office purposes, including insufficient data bandwidth, and a sense of reduced motivation and effort. Although our data indicate that face-to-face contact was greatly missed during this time-period, a thoroughly planned online course with numerous contact points between teachers and students would likely have been received more favorably. Finally, the students expressed that they wanted more structure in future digital courses. Due to the very unusual circumstances experienced both by students and teachers in the early stages of national lockdown in Norway, we are hesitant to conclude with regards to students preferences for future online courses.

Supporting information

S1 file. spss file questionnaire 1—please see line 154..

https://doi.org/10.1371/journal.pone.0250378.s001

S2 File. SPSS file Norwegian questionnaire 1—please see line 154.

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S3 File. SPSS file questionnaire 2—please see line 154.

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S4 File. SPSS file Norwegian questionnaire 2—please see line 154.

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S5 File. Structured interview guide–please see line 145.

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Acknowledgments

The authors would like to thank the participating students and the academic and administrative staff at Oslo Metropolitan University for their contributions.

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The COVID-19 pandemic has changed education forever. This is how 

With schools shut across the world, millions of children have had to adapt to new types of learning. Image:  REUTERS/Gonzalo Fuentes

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Farah lalani.

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Getting Recommendation Letters During COVID-19

Here are some tips on how to manage this critical part of the college admissions process virtually.

COVID-19 and Recommendations Letters

In the eyes of a college admissions officer, there are layers to consider beyond grades alone, and teachers can help paint a poignant picture. (Getty Images)

With SAT or ACT test scores for first-year college applicants no longer required by many universities due to the coronavirus pandemic, students' attention is shifting to maximizing the effectiveness of their recommendation letters in order to stand out .

Writing About COVID-19 in College Essays

Josh Moody Oct. 21, 2020

While new challenges of remote learning and disrupted school calendars have brought some distractions to teachers – who are adapting to a whole new way of working – students who act now and secure strong recommendations can seize the opportunity to amplify the letters' effectiveness in their overall college application .

Now more than ever, teacher recommendations bring credibility and a nuanced perspective on which admissions officers can base their decisions, says Benjamin Schwartz, a former assistant director of admissions at Dartmouth College in New Hampshire and co-founder of the Sage Experience leadership development program based in Ghana.

"Teacher recommendations have always been a critical component of the application, allowing us to understand a student's academic and intellectual story behind the basic grades," Schwartz wrote in an email. "Now with some schools and districts awarding Pass/Fail, and complicating factors in the lives of many students, the teacher recommendation only takes on even more importance for many applicants."

The key to maximizing the effectiveness of teacher recommendations amid COVID-19 is inclusivity and connection, Schwartz says.

"I have always encouraged students to get to know their teachers. The teacher recommendation is a way for us to know that the student cares about more than grades and is ready to add thoughtful insights and contributions to the classroom and broader community," he says.

Lauren Bayersdorfer, a math teacher in the Weehawken Township School District in New Jersey who specializes in teaching algebra and AP Calculus, says letters of recommendation provide admissions officers with insights into how an applicant will perform as a student and member of the college community.

"Although standardized tests are a way to see what a student has learned in content areas, it is very difficult for admissions officers to see what a student is truly like as a person," Bayersdorfer wrote in an email. "Recommendation letters are always valuable in conveying that subjective and more personal perspective, but they are especially important this year, as meaningful relationships may (arguably) be more important than math standards."

"Universities are able to get a more intimate understanding of a student as a whole person and their possible struggles during this time rather than just another applicant with a score out of 1600," Bayersdorfer adds, referencing the SAT.

As many schools started this academic year 100% virtually and without in-person interaction , students and teachers are having to put in extra effort to connect virtually. The question on many seniors' minds is, "How can I build rapport with teachers to facilitate effective teacher recommendations while distance learning?"

Bayersdorfer says visibility can go a long way. "This may sound very simple, but from a teacher's perspective, turn your camera on once in a while. It is sometimes defeating to teach to a screen full of black muted squares and it's enlightening to see a face on the other side of my talking."

She adds: "I'm one month into the school year, and I still haven't seen the faces of some of my students. Even though it may feel embarrassing for students to take themselves off mute and ask questions virtually, it helps everyone and builds a classroom community that is so difficult to do virtually."

In the eyes of a college admissions officer, there are layers to consider beyond grades alone , and teachers can help paint a poignant picture.

"When asking a teacher for a letter of recommendation, it's important, not so much that you (the student) obtained an A in that class, but that you feel as though you did everything you could to do well in that class," Bayersdorfer says.

"As teachers, we want our letters to be genuine and accurately reflect the student. In having written several letters of recommendation, I always seek to include information that highlights qualities that make the student an individual, in relation to the successes they were able to have in their four short years," Bayersdorfer says.

Experts suggest three letters total – two from different teachers and one from an administrator or counselor. The recommendation letters should be from educators who know the student well and have taught him or her in the last two years of rigorous academic courses. An administrator could be a principal or school counselor .

Teachers and college admissions officers suggest five ways for students to secure strong recommendation letters during COVID-19:

• Form a social connection beyond the classroom.
• Host an online extracurricular club.
• Poll teachers for feedback.
• Generate publicity and invite teachers to comment.
• Take the time to be as personal in the request as possible.

Form a Social Connection Beyond the Classroom

Students should consider who the recommenders are and prioritize connecting outside of class. Ideally, the teachers know the student academically and personally, and can highlight his or her strengths. Recommenders should be able to speak on behalf of a student's character and performance as a school and community member.

Students should keep in mind that letters of recommendation may be required ahead of the college application process. From his experience seeking teacher recommendations for summer programs, Andy Lau, a junior at Homestead High School in California, suggests carefully selecting teachers based on current interactions. "Do you have an active interest in the class? If you have an active interest in the subject, you are more likely to ask more questions and participate in class," he wrote in an email.

"By taking an active interest in the subject and applying it to your daily life, you form a social connection beyond the classroom," he adds. "More importantly, it also gives plenty of memorable moments and personal qualities for your teacher to include in the recommendation letter."

Lau is targeting teachers with whom he has stayed after class to get extra help or discuss course materials. "I am currently considering requesting a letter of recommendation from my child developmental psychology teacher because I often stay after class and discuss how topics apply to my past or daily life," he says.

"Moreover, if you stay after class, the teacher will get to know you better, and especially during COVID-19, this will make your recommendation stand out."

Host an Online Extracurricular Club

Not only does forming a club allow students to scale their extracurricular initiative rapidly, it also makes the process of inviting recommenders easier, some experts say.

As observers of virtual meetings, teachers and administrators can gauge the role a student played in launching the activity and how he or she transformed the initiative over time. They also can provide coaching and mentorship to the student and to peers if there is a committee or club involved.

Students who take on leadership roles should be sure to analyze growth data so they can use numbers to speak to their work when soliciting letters of recommendation.

Poll Teachers for Feedback

Build buy-in by having teachers invest time in providing feedback on topics such as the name of the new initiative, the type of promotional elements to invest in or the format in which a competition can run, if that applies. This will bring them closer to the project.

Generate Publicity and Invite Teachers to Comment

Students can elevate the impact of their leadership by pitching stories on initiatives to local news outlets and securing coverage in a school publication.

Inviting teachers to provide comments naturally allows them to become closer to the project and witness firsthand its impact and growth. A fact sheet and background statement that summarize the project can also be provided to aid in writing a recommendation letter.

Take the Time to Be as Personal in the Request as Possible

Students should explain why they chose to ask the teacher or counselor to write a letter of recommendation and detail their goals for college and beyond, experts say. Students should also let recommenders know the particular points they would like them to consider when writing the letter – including the course taken – and share their broader application narrative. They can include any key terms that they hope college admissions officers will associate with them.

It's also good for students to remember to offer any support that recommenders need throughout the process, being mindful to work within teacher office hours that may have shifted during the pandemic.

"I would first schedule an office hours appointment where you can have a one on one conversation with your teacher," Lau says. "If this is not possible, then emailing a polite email is not ideal, but an option."

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Original research article, covid-19 pandemic and student reading achievement: findings from a school panel study.

• 1 Center for Research on Education and School Development (IFS), TU Dortmund University, Dortmund, Germany
• 2 Department of Educational Psychology, Goethe University Frankfurt, Frankfurt, Germany

Since 2020, the COVID-19 pandemic had an impact on education worldwide. There is increased discussion of possible negative effects on students’ learning outcomes and the need for targeted support. We examined fourth graders’ reading achievement based on a school panel study, representative on the student level, with N  = 111 elementary schools in Germany (total: N  = 4,290 students, age: 9–10 years). The students were tested with the Progress in International Reading Literacy Study instruments in 2016 and 2021. The analysis focused on (1) total average differences in reading achievement between 2016 and 2021, (2) average differences controlling for student composition, and (3) changes in achievement gaps between student subgroups (i.e., immigration background, socio-cultural capital, and gender). The methodological approach met international standards for the analysis of large-scale assessments (i.e., multiple multi-level imputation, plausible values, and clustered mixed-effect regression). The results showed a substantial decline in mean reading achievement. The decline corresponds to one-third of a year of learning, even after controlling for changes in student composition. We found no statistically significant changes of achievement gaps between student subgroups, despite numerical tendencies toward a widening of achievement gaps between students with and without immigration background. It is likely that this sharp achievement decline was related to the COVID-19 pandemic. The findings are discussed in terms of further research needs, practical implications for educating current student cohorts, and educational policy decisions regarding actions in crises such as the COVID-19 pandemic.

Introduction

Since the beginning of 2020, the COVID-19 pandemic has led to a substantially new situation for education systems. To contain the spread of the virus that causes COVID-19, schools in many countries around the world have partially or completely closed, learning groups have been rearranged, and students or teachers had to be absent from school for various amounts of time (cf., Woessmann et al., 2020 ; Meinck et al., 2022 ). Teachers had to carry out learning activities without the usual face-to-face lessons, learners had to self-regulate at home, and parents had to support their children’s learning more than before. How these learning conditions affected students’ achievement is of considerable interest for educational policy, administration, and practice. This is especially true for reading literacy, a key competence that influences students’ achievement in other subjects and enables them to participate in society throughout their entire life course. Additionally, there is reason to assume that the COVID-19 pandemic had a differential effect on students. Even within a given education system, certain groups of students might have been affected more severely than others.

In Germany, the sudden shift from face-to-face instruction to more technologically mediated interaction and emergency remote education (ERE) was especially hard. ERE required German schools and teachers to catch up in terms of the digitalization process in education, which had been shown to lag behind other countries in the years prior to the pandemic (cf., Voogt and Roblin, 2012 ; Eickelmann et al., 2019 ; Lorenz et al., 2021 ). Studies have repeatedly shown that teachers lacked pedagogical skills related to technology and that students had problems accessing and using technological devices during the COVID-19 pandemic (e.g., Huber and Helm, 2020 ; Reimers and Schleicher, 2020 ; Rožman et al., 2022 ). Therefore, Germany might have had particular problems in adapting to the pandemic schooling situation.

A variety of recent publications have shown that schools, instruction, and stakeholders—school administrators, teachers, students, and parents—were only partially prepared for a crisis with substantial restrictions on school life such as the COVID-19 pandemic (e.g., Huber et al., 2020 ). Accordingly, teachers as well as parents subjectively perceived a decline in student learning ( Dong et al., 2020a ; Rožman et al., 2022 ). In contrast, some studies based on student reports found (tendentially) positive learning experiences compared to usual instruction, but students pointed out that they felt more uncertain about estimating their learning status (e.g., Huber and Helm, 2020 ; Rožman et al., 2022 ). However, there is a lack of country-specific results related to effects of the COVID-19 pandemic on key achievement measures via standardized tests. Highly aggregated results show that school closures due to COVID-19 had an effect of about d  = −0.08 ( Hammerstein et al., 2021 ) and d  = −0.17 ( König and Frey, 2022 ) on average student achievement across subject areas, grades, and countries. Data for Germany regarding achievement in one domain that is generalizable to a well-defined student population is missing so far.

Elementary school, and fourth grade in particular, is a pivotal moment in students’ educational biographies. At this point, reading literacy should be developed to the point where students can acquire further knowledge through reading in all subjects and continue their educational biography through independent learning. Additionally, in most federal states in Germany, after 4 years of compulsory elementary education (Grades 1–4 in age-homogenous classes of 21 students on average; Destatis, 2018 ), typically starting at age 6, students finish elementary school and go on to secondary schools of different tracks ( Lohmar and Eckhardt, 2015 ). At the end of elementary school, studies before the COVID-19 pandemic repeatedly indicated that disadvantaged student groups exhibit lower reading literacy (e.g., Mullis et al., 2017 ). The COVID-19 pandemic might pose further risks for successful education, especially for disadvantaged student subgroups.

Taken together, students’ achievement level in important areas (e.g., reading) is of special interest after a long period of restrictions related to the COVID-19 pandemic. Additionally, whether achievement differences between student subgroups are currently greater than before is an important research question. To provide reliable comparative information on key competences before and during the COVID-19 pandemic, the present study examined reading achievement among fourth graders in German elementary schools. In this study, samples representative for the student population of all fourth graders in Germany were examined in the same 111 elementary schools in 2016 and 2021. Both samples were tested with the reading achievement tests from the international school achievement comparison study Progress in International Reading Literacy Study (PIRLS). We accounted for changes in student composition and investigated achievement means and how achievement gaps have evolved.

Reading Achievement

The acquisition of reading literacy is key for further learning in other school subjects and students’ subsequent educational and life paths ( Savolainen et al., 2008 ). Reading achievement is a core component of reading literacy, along reading motivation and behavior. In international achievement studies such as PIRLS, reading achievement represents students’ ability to extract relevant information from narrative and informational texts and to understand, use, and reflect on written texts in areas of life that are relevant to the individual and required by society ( Mullis et al., 2015 ). Reading achievement involves multiple levels of text comprehension: surface structure, text base, situation model, rhetorical structure, and pragmatic communication ( Kintsch, 1988 ; Graesser and McNamara, 2011 ). Mastering text comprehension requires sufficient word recognition (e.g., decoding skills; Wang et al., 2019 ), language comprehension (e.g., verbal reasoning), and bridging processes (e.g., vocabulary knowledge; see Kim, 2020 ), as well as active self-regulation, motivation, and engagement ( Duke and Cartwright, 2021 ).

In the first years of schooling, students learn to read at the letter, word, and sentence level in the sense of automating reading and propositional comprehension processes. By the end of fourth grade, which is the end of elementary school in most German federal states, students are expected to comprehend increasingly longer and more complex texts (e.g., Fitzgerald et al., 2015 ) and to build situation models for age-appropriate texts.

There are important differences concerning comprehension of narrative and informational texts when it comes to different subprocesses (e.g., Ozuru et al., 2009 ). However, for pragmatic reasons, many comparative studies report on global reading achievement (e.g., Mo, 2019 ) that reflects comprehension of narrative and informational texts as well as other genres.

Reading and the Impact of the COVID-19 Pandemic

Various factors must be considered in ascertaining whether and to what extent reading achievement has been affected by the restrictions related to the pandemic. Students learn to read via formal school-based instruction, including homework, and in their leisure time through informal reading activities. The transition from face-to-face instruction in school to ERE because of the COVID-19 restrictions led to less time for formal school-based instruction ( Reimers and Schleicher, 2020 ). In addition, there was less instructional time available in ERE, so that overall students spent less time on learning than they would have in school ( Woessmann et al., 2020 ). In Germany, compared to before the time spent on learning activities dropped by 62% and 42% during the first and second lockdown phases (spring 2020 and autumn/winter 2020/2021), respectively ( Woessmann et al., 2020 ; Werner and Woessmann, 2021 ). At the same time, students’ leisure time behavior partly changed during ERE ( Grewenig et al., 2020 ; Woessmann et al., 2020 ): the time spent on reading activities, creative work, and exercise stayed on a comparable level during the school closures in Germany (spring 2020: +11%; autumn/winter 2020/2021: −14%). But the time spent on screen-based activities such as watching TV, gaming, social media, and online media increased by a notable 21% (spring 2020) to 34% (autumn/winter 2020/2021). Children from non-college-educated households spent 1 h more on such screen-based activities than children from college-educated households ( Woessmann et al., 2020 ). The reduction in total time spent on formal and informal reading activities and the shift toward more screen-based activities may have affected students’ achievement in reading.

Besides these substantial reductions in learning time, reading development could be negatively affected by the reduced effectiveness of instruction during the pandemic. Reading instruction could have been hampered by limited experience with technical equipment necessary for digital instruction and learning during ERE (e.g., Reimers and Schleicher, 2020 ; Rožman et al., 2022 ). This problem had been recognized in Germany even before the COVID-19 pandemic (e.g., Lorenz et al., 2021 ). Compared to other subjects, there are less rigorous curricular frameworks and less readily available exercises, instruction, and materials for reading teachers when reading is done (in part) at a distance ( Maldonado and De Witte, 2020 ). Additionally, fourth graders are confronted with informational texts that involve new challenges, for instance, an increasing amount of instructional pictures (e.g., graphs, maps, and diagrams). This new challenge of cognitively demanding integrated text-picture comprehension might be difficult for teachers to support in distance learning situations ( McElvany et al., 2012 ; Hochpöchler et al., 2013 ).

Currently, there is no differentiated picture of student achievement, and particularly of elementary school children’s reading achievement, during or after the restrictions related to the COVID-19 pandemic compared to before the pandemic. Several publications have already dealt with the effects of the COVID-19 pandemic on students in terms of wellbeing, school achievement, and their interactions (e.g., Hammerstein et al., 2021 ; Rose et al., 2021 ; Sánchez Amate et al., 2021 ). Different approaches were pursued, including a focus on theoretical considerations (e.g., Schneider et al., 2021 ), teacher surveys (e.g., Reimers and Schleicher, 2020 ; for Germany: McElvany et al., 2021 ), and parent surveys (e.g., Reimers and Schleicher, 2020 ; Steinmayr et al., 2021 ).

In a first systematic review on student achievement across multiple countries and grades, Hammerstein et al. (2021) focused on the effects of school closures related to COVID-19 on the subjects of math and reading. They reported heterogeneous effect sizes ( d  = −0.37 to d  = 0.25) across studies, with a small negative effect (median d  = −0.08) on average. These results for the first lockdown phase were corroborated by two meta-analyses. König and Frey (2022) reported an average impact of d  = −0.12 of later school closures (after summer 2021) on average student achievement. Storey and Zhang (2021) found an effect of d  = −0.15 across domains. Furthermore, Zierer (2021) found an average effect of d  = −0.17 for elementary school students. Among studies examining reading achievement in elementary school children, two studies ( Depping et al., 2021 ; Gore et al., 2021 ) reported very small positive effect sizes ( d  = 0.00 to d  = 0.04). In contrast, the four studies finding negative effects on reading achievement reported larger but still small effect sizes ( Engzell et al., 2021 : d  = −0.09; Maldonado and De Witte, 2020 : d  = −0.29; Schult et al., 2021 : d  = −0.07; Tomasik et al., 2020 : d  = −0.37). However, it is not yet known how the situation during the COVID-19 pandemic affected reading achievement in elementary school in Germany as a whole.

Reading Achievement Gaps

International large-scale assessments of student achievement have repeatedly shown that Germany has some of the most pronounced social disparities ( Hußmann et al., 2017 ; Reiss et al., 2019 ). There are several theories offering explanations for gaps in achievement related to family background and student variables such as gender (e.g., primary and secondary effects: Boudon, 1974 ; Grätz and Wiborg, 2020 ; expectancy-value approaches: Wigfield and Eccles, 2000 ; Guo et al., 2015 ; cultural theory: Bourdieu, 1983 ; and motivation as mediator: Wang and Finch, 2018 ; Steinmayr et al., 2021 ). When examining the relationship between family background and reading achievement, studies often refer to socio-cultural capital and the immigration background. Additionally, reading achievement and reading motivation are known to be systematically related to gender ( Wigfield et al., 2016 ).

Family Background

Children with different family backgrounds experience different levels of support from home and their reading socialization varies accordingly. Following the home literacy model ( Sénéchal and LeFevre, 2002 ), such support may involve different literacy experiences, for instance shared reading between parents and children, teaching the alphabet, or reading words. These literacy experiences explain children’s growth in reading and vocabulary knowledge (e.g., Becker et al., 2010 ). Among other factors, these home literacy experiences could explain that the reading achievement of children and adolescents in Germany and many other countries is systematically associated with family background characteristics, such as socio-cultural capital or immigration background ( Mullis et al., 2017 ; for Germany: Wendt and Schwippert, 2017 ).

Socio-Cultural Capital of the Family

Socio-cultural capital describes the social assets of a person (e.g., intellect and education). More highly educated parents are often able to support their children better and promote their children’s reading socialization more comprehensively, due to their own educational experiences and by being educational role models ( Dong et al., 2020b ). Therefore, higher socio-cultural capital is positively associated to reading achievement.

The number of books at home has become a frequently used indicator to approximate socio-cultural capital in large-scale assessments (e.g., Schwippert, 2019 ). There are large differences in reading achievement between children from families with different amounts of books at home in many countries (international: Mullis et al., 2017 ). In Germany, children from families with more than 100 books at home have substantially higher reading achievement on average, than children from families with a maximum of 100 books at home ( Hußmann et al., 2017 ). There are different mechanisms that could explain these differences. (1) More books at home represent an opportunity for children to engage in reading. (2) Parents with more books are more likely to read by themselves, making them positive role models. (3) Furthermore, they are probably able to support their children to a higher degree. (4) The presence of books indicates parents’ appreciation for reading and intellectual stimulating activities and (5) is associated with a relatively stable, wealthy and spacious living situation. In sum, the amount of books at home represents a broad indicator for a family background with favorable conditions for becoming a good reader.

Immigration Background

On the one hand, families from immigrant backgrounds often place high value on and strongly promote their children’s education, as suggested by the immigration optimism hypothesis ( Kao and Tienda, 1995 ). On the other hand, an immigrant background can also represent a challenge, as it is often confounded with a lower socioeconomic status, a lack of experience with the education system in the host country, and a different family language than the language of instruction, which is associated with children’s lower language skills on average ( Kristen and Dollmann, 2012 ; Mullis et al., 2017 ). Immigrant parents often do not speak the language of instruction as well as native speakers, so their children may not learn the language implicitly to the same extent as their classmates, which could also affect their reading skills. This is supported by the results of PIRLS 2016, where children who always or almost always spoke German at home scored substantially higher on average than children who never or almost never spoke German at home ( Wendt and Schwippert, 2017 ; for an in-depth longitudinal analysis, see Kigel et al., 2015 ).

Prior to 2021, Germany underwent a number of societal developments that have affected education. One such development is an increase in the number of immigrants coming to Germany. In 2020, about 24 percent of people living in Germany had an immigrant background. Among 5–10 year-old, 38.8 percent of children have a primary or secondary immigration background. This proportion increased by 2.7 percentage points compared to 2019 ( Destatis, 2021 ).

Several theoretical approaches have attempted to explain gender differences in reading achievement (for an overview of gender differences in reading and language, see Eagly and Wood, 1999 ; Hyde, 2014 ). For example, socio-cultural theory explains differences based on societal stereotypes regarding reading and learning activities ( Schunk and Zimmerman, 2006 ). According to social-cognitive learning theory, the gender gap in reading can be explained by girls’ better self-regulatory abilities and their higher self-efficacy (cf., Hyde, 2014 ; McElvany et al., 2017 ). Additionally, reading achievement is substantially related to reading motivation ( Toste et al., 2020 ). On average, girls have higher reading motivation and read more often in their leisure time ( Ainley et al., 2002 ; Wigfield et al., 2016 ; Lepper et al., 2021 ), which promotes their reading achievement. Thus, a wealth of studies indicate that girls have a higher level of reading achievement than boys on average ( Logan and Johnston, 2010 ; Mullis et al., 2017 ). The PIRLS 2016 results for Germany showed that fourth grade girls scored systematically higher than boys; the achievement gap favoring girls in Germany was about the same as the average achievement gap in the EU and OECD countries overall ( McElvany et al., 2017 ).

Reading Achievement Gaps and the Impact of the COVID-19 Pandemic

To date, there is no clear evidence on how the restrictions related to COVID-19 influenced reading achievement gaps among elementary school students. It is possible that the COVID-19-related restrictions had differential effects for different subgroups of students and therefore exacerbated educational inequality. Generally, the aforementioned achievement differences related to students’ socio-cultural capital, immigrant backgrounds, and gender can be expected to hold for the COVID-19 pandemic period as well. In fact, they may be even more pronounced because school-based support was difficult during full or partial school closures and children’s learning was left in the hands of families to a greater extent than before the pandemic (e.g., Huber and Helm, 2020 ). For students with lower socio-cultural capital and/or from immigrant backgrounds, the need for greater parental involvement in the learning process might have led to widening achievement gaps. As described above, parents with more socio-cultural capital are more engaged and provide more support for their children’s learning ( Dong et al., 2020b ). Therefore, it seems plausible that children from these families might benefit from spending more time learning with their parents. With respect to immigrant families, if learners speak a language other than the language of instruction at home, they may receive inadequate support in the language of instruction, which is particularly important for reading achievement and might have therefore affected educational outcomes in this domain during or after the COVID-19 pandemic (see Maldonado and De Witte, 2020 ). ERE was associated with additional costs if families had to purchase technological devices for their children to participate in the digital lessons. This may have further disadvantaged students from low-income families ( Eickelmann et al., 2019 ; Wrase, 2020 ). Regarding gender, a widening achievement gap might be expected, as female students tend to have higher reading motivation and more frequently read for pleasure than male students (e.g., McElvany et al., 2017 ; Mullis et al., 2017 ). A decline in extrinsic school-based reading motivation during the COVID-19 pandemic may have led to these gender differences playing a greater role in reading improvement, which could exacerbate gender achievement gaps in the current cohort of students. Empirical evidence has shown that students’ leisure time behavior changed during the COVID-19 pandemic (e.g., Woessmann et al., 2020 ; Werner and Woessmann, 2021 ), which could affect the trends in achievement gaps. Students with more highly educated parents spent less time on leisure activities detrimental to learning than their peers and more time on conducive activities ( Grewenig et al., 2020 ; Woessmann et al., 2020 ). First evidence by Engzell et al. (2021) shows a 40% larger learning loss among students from poorly educated families compared to children from highly educated families in the Netherlands.

Current Study and Research Aim

The COVID-19 pandemic affected many areas of education, resulting in a need for empirical research how students’ learning was affected during this time. First studies indicate negative effects on students’ learning outcomes and learning behavior due to the COVID-19 restrictions. More differentiated results on reading achievement among German elementary school students are lacking so far.

The aim of this study is to provide more differentiated results on trends in elementary school students’ reading achievement by applying rigorous methodological standards and using data from a school panel study. Differences in reading achievement across different cross-sectional cohorts may be explained by changes in student composition, even when the same schools participate. Thus, the present study also controlled for changes in the student composition within each school. Furthermore, the development of reading achievement gaps during the pandemic was investigated. The students examined in this study are representative for fourth graders in Germany. We used the reading achievement tests from PIRLS 2016.

The research questions and hypotheses investigated are as follows:

1. How does the average reading achievement of fourth grade elementary school students in Germany differ in 2021 compared to before the COVID-19 pandemic in 2016?

H1 : Due to theoretical considerations on the impact of COVID-19-related restrictions on schooling, we expect a decline in average reading achievement from 2016 to 2021.

2. How does the average reading achievement of fourth grade elementary school students in Germany differ in 2021 compared to before the COVID-19 pandemic in 2016 after controlling for student composition?

H2 : We expect a decline in average reading achievement from 2016 to 2021 even when adjusting for student composition.

3. Considering achievement gaps between subgroups of students, (3a) to what extent do differences in reading achievement exist across student subgroups (socio-cultural capital, immigration background, and gender) in 2021 and (3b) how do these gaps differ in 2021 compared to 2016?

I. There is a gap in average reading achievement to the disadvantage of students with lower socio-cultural capital (H3.1.1) and this gap is larger in 2021 than in 2016 (H3.1.2).

II. There is a gap in average reading achievement to the disadvantage of students from immigrant backgrounds (H3.2.1) and this gap is larger in 2021 than in 2016 (H3.2.2).

III. There is a gap in average reading achievement to the disadvantage of boys (H3.3.1) and this gap is larger in 2021 than in 2016 (H3.3.2).

Materials and Methods

Participants.

The target population for the school panel analyses was the cohort of fourth graders attending a general education German elementary school (i.e., one that does not cater exclusively to special education students) that existed in both 2016 and 2021 (i.e., excluding closed and newly founded schools). The analysis was based on the responses of N  = 2,208 fourth grade students in 2016 and N  = 2,082 fourth grade students in 2021 from a panel of N  = 111 general education schools (with one class per school participating). All schools participated in PIRLS 2016 and were examined again 5 years later for the school panel study. Participation in the reading achievement test was mandatory in both years. Students required parental consent to fill out the student background questionnaire. Students with intellectual or physical disabilities (e.g., blindness or deafness) and recently immigrated children with less than 1 year of German instruction were free to participate but were excluded from the data set.

Data collection in 2021 was slightly affected by the COVID-19 pandemic and took place four to 6 weeks later in the school year than in 2016 (May 2 to June 3, 2016, vs. June to July 3, 2021). The absence rate on the test day was slightly higher in 2021 compared to 2016 (6.03% in 2016 vs. 9.01% in 2021). In 2021, at the time of the study, students were required to stay home at the first sign of illness. We will discuss possible consequences for the interpretation of the results later.

Sampling Procedure

PIRLS 2016 followed a two-stage (i.e., sampling first schools and then classes within schools) stratified cluster design ( Martin et al., 2017 ). In 2016, a total of 208 schools were randomly sampled from a complete list of elementary schools in Germany, considering strata regarding school type (e.g., general education vs. special education schools) and the proportion of students from immigrant backgrounds as well as the additional condition that at least one school from each German Federal State had to participate. In 2021, 116 schools were sampled for the panel study as a random sample of the original N  = 208 schools in PIRLS 2016, considering the strata school type and proportion of children from immigrant backgrounds. For the analysis, we excluded special education schools ( n  = 5) because they are structurally very different from general education schools (i.e., much smaller classes, less bound to state-mandated curricula, and students do not transition to secondary schools after fourth grade). This resulted in a sample of N  = 111 general education elementary schools.

The overall weights were calculated to adjust for clustered sampling (i.e., at the school level), the combination of school, class and student weights, as well as non-response adjustment at each level ( Martin et al., 2017 ). On average, each student in our sample from 2016 represented 294 students in the target population for 2016, and each student in our sample from 2021 represented 325 students in the target population for 2021. The 2016 sample represented 648,297 and the 2021 sample 677,762 students.

Instruments

Reading achievement test.

The reading achievement test used in PIRLS consisted of six narratives and six informational texts and different comprehension tasks developed for them ( Mullis et al., 2015 ; Martin et al., 2017 ). In 2016, 181 items were administered across 15 different test versions, with each student answering items about two texts. The reading achievement test in 2021 was a subset of 120 items of the test in 2016, spread over eight different booklets. Each student answered 28.31 items on average ( SD  = 4.70) in 2016 and 27.24 items on average ( SD  = 4.50) in 2021. The items were a mixture of multiple-choice (MC) and constructed response (CR) items. The MC items were scored as either correct or incorrect. CR items were rated by trained personnel from the study administration based on scoring rubrics, as either incorrect, partially correct, or completely correct. Omitted items were scored as if they were incorrect responses and not reached items were treated as if they were not administered. The overall scoring procedure was the same in 2016 and 2021. More details on test construction can be found in Martin et al. (2017) .

Student Composition Variables

All of the following variables are based on questions asked in both cycles (i.e., 2016 and 2021) with the same phrasing, at a similar location in the questionnaire, to the same group of respondents (i.e., students, teachers, parents, and school administrators). For binary variables, we chose a coding that sets the majority group (>50%) to 0 and the minority group (<50%) to 1, unless indicated otherwise.

The gender variable was based on administrative data indicating students’ gender as reported in official documents. We used contrast coding for gender, because there is no majority group (1 = Male; −1 = Female). A third category (i.e., “Other”) was only collected in 2021 and not in 2016 and could therefore not be considered in the analysis.

Age, Enrolment, and Grade Retention

We aimed at comparing same-aged students in 2016 and 2021. Generally, students’ age within and across cohorts of fourth graders in Germany is biased by school enrolment deadlines in Germany’s federal school system (i.e., the deadlines by which students have to turn 6 years old in order to enroll in first grade in a given year vary from August 5 to September 30 across different federal states). Additionally, the average age of participating students is higher in 2021 due to the fact that the survey period shifted slightly toward later in the school year. Furthermore, individual students’ age in fourth grade depends on whether they enrolled in school late or early relative to their birth date, and whether they were held back a grade during elementary school. Generally, being older relative to the rest of a cohort could be a developmental advantage, whereas late enrolment and grade retention are negatively associated with achievement (e.g., Bell et al., 2009 ). Based on these considerations, we used three variables to control for age-related aspects:

1. Relative cohort age: Students’ age within a cohort in a federal state, excluding individual deviations from regular enrolment (i.e., enrolment at age 6) and excluding grade retention. This variable represents a child’s age if all federal states had the same enrolment deadline and excludes age shifts of entire years caused by irregular enrolment and grade retention. This age variabe had a range of 1 year.

2. Enrolment: Individual deviations from regular school enrolment in years (regular enrolment is at age 6; deviations would include enrolment at age 5 or 7).

3. Grade retention: Individual deviations in the number of years of schooling in years (regular is four).

We chose to define immigration background in three different ways based on the students’ responses.

1. The student was not born in Germany (=1) vs. the student was born in Germany (=0).

2. One or both of the students’ parents were not born in Germany (three-level factor with both parents born in Germany as the reference group: both parents born in Germany, one parent not born in Germany, and both parents not born in Germany). Place of birth for both the mother and father had to have been filled in; otherwise, the variable was set to missing.

3. The student’s family almost never or never speaks German at home (=1) vs. the family almost always or always speaks German at home (=0).

Socio-Cultural Capital

We used students’ responses regarding the number of books at home to approximate their cultural capital. The first group included students who reported that their families owned 100 books or less (=1) vs. students who reported that their families possessed more than 100 books (=0).

Special Educational Needs

In Germany, students with special educational needs have been diagnosed by an official institution as having a disability that necessitates special learning support. Specific disorders regarding scholastic skills such as dyslexia do not qualify a student for special educational support. We distinguish students with no special educational needs (=0) from students with diagnosed special educational needs (=1).

PIRLS 2016 and the 2021 panel study were administered by the International Association for the Evaluation of Educational Achievement (IEA) in Hamburg. Both studies were conducted entirely on paper and took place during the first half of the school day. The study was administered by trained test administrators in each class, assisted by a teacher known to the class. The test administrators were university students from related disciplines (teacher training, educational science, and psychology) who attended a mandatory workshop on international testing guidelines and the standardized testing manuals.

The testing procedure was structured the same in both cycles. First, students worked on the PIRLS achievement test in two 40-min blocks with a 10-min break in between. During these blocks, students were allowed to ask questions to clarify the instructions but not regarding how to solve the tasks. Second, after another break, students completed several further standardized tests (for cognitive ability, decoding, vocabulary, and sentence comprehension). The cognitive ability test was administered with different variations in the two cycles (e.g., different time constraints), and different instruments were used to assess the reading subprocesses, so we did not use them for the analyses presented here. Lastly, to obtain background information, students completed a questionnaire that took 45 min for PIRLS 2016 and 60 min for the panel study 2021. However, the fact that the questionnaire was longer in 2021 was not relevant to our analysis because all the questions we were interested in (immigration background and socio-cultural capital) were at the beginning of the questionnaire. In total, the study took 138 min in 2016 and 160 min in 2021, mainly because of the longer questionnaire at the end of the study.

Data Analysis

Data preparation and analyses were performed using R Studio Version 4.0.3 ( R Core Team, 2020 ). First, we used multi-level imputation to treat missing data in the background variables. Second, we scaled the test data using a multi-group IRT model. Third, plausible values were drawn based on the imputed background variables for conditioning. Fourth, we used linear mixed-effects models to examine our research questions.

Missing Values and Multiple Imputation

We used multiple imputation to address missing values occurring in our data. All student composition variables are based on either administrative data (e.g., age and gender) or students’ responses (e.g., books at home and immigration background). For administrative variables, the missing rate was very low, <1%. In 2016, about 10% and in 2021, about 12% of student responses on the background questionnaire were completely missing (i.e., mostly due to missing parental consent). Missing student responses were not systematically clustered within classes.

The multiple imputation was carried out separately for 2016 and 2021 with the same variables and specifications. In addition to student composition, we included parents’ reported number of books at home from the parent questionnaire and city size as auxiliary variables. For the imputation, we used a two-level imputation with predictive mean matching at level one for continuous variables (e.g., age). Furthermore, we used predictive mean matching for level two variables (i.e., city size) and logistic regression for binary variables (i.e., immigration background) within the R packages miceadds ( Robitzsch et al., 2017 ) with 20 iterations and 10 imputed datasets.

Scaling and Plausible Values

Scaling for the reading achievement test was performed using a multi-group generalized partial credit model ( Van der Linden, 2016 ). The model was estimated using the marginal maximum likelihood method (MML) with the R package TAM ( Robitzsch et al., 2019 ). The model estimates a difficulty and a discrimination parameter for each item or response category. Prior to model estimation, we excluded two items because fewer than 5% or more than 95% of responses were correct (i.e., leaving 179 items for 2016 and 118 for 2021). The slopes within each CR item with multiple response categories were set to be equal to each other. We used a multi-group approach instead of separate scaling with linking because the achievement tests and test procedures in 2021 and 2016 were very similar. All items had a root mean squared deviation (RMSD) <0.08, so that none of the items indicated large misfit ( Köhler et al., 2020 ). Because the item fit was acceptable for all included items, we considered the multi-group approach to be appropriate. The EAP reliability was good at REL EAP  = 0.87. For all analyses, we used 10 plausible values to provide a measurement error-adjusted and unbiased estimation of effects. Plausible values were drawn using item parameters anchored at their estimated values from the calibration and random draws from the marginal posterior of the latent distribution for each student ( Monseur and Adams, 2009 ). We used all student composition and auxiliary variables as well as their interaction with the cycle (2016 vs. 2021) for conditioning. We performed five draws with each of the 10 sets of imputed conditioning variables, resulting in 50 data sets. Finally, we used a scale that sets the mean and SD in 2016 to 1,000 and 100, respectively, to make the results of the reading achievement test easier to interpret.

Proportions, means, and SDs were calculated with multiple imputed variables, overall student weighting and school clustering using the R package survey ( Lumley, 2020 ).

Students’ reading achievement was statistically modeled using a linear mixed-effects model framework in the R package lme4 ( Bates et al., 2014 ) with the weights for 2016 and 2021. We estimated three models: (1) a gross differences model (i.e., without student composition) to compare the overall difference between the study cycles (2016 vs. 2021) and a (2) net differences model that considered changes in student composition. Additionally, we estimated (3) an achievement gap model that considers possible changes in the achievement gaps.

First, we modeled the reading achievement (θ pc ) of a student p  = 1, …, N in school c  = 1, …, C using a linear mixed-effect model ( Bates et al., 2014 ). In the gross model (GM), reading achievement was modeled as a function of an intercept β 0 (i.e., the average reading achievement in 2016), the fixed effect of the year β cycle (0 = 2016, 1 = 2021), and the random intercept of the school ζ c [the variance of ζ c was normally distributed with ζ c  ~  N (0, σ 2 ζ)]. Thus, in our GM, β 0 represented the average reading achievement in 2016 and β cycle the difference between 2021 and 2016.

Second, the net model (NM) included all student composition variables ( X pk ), k  = 1, …, K as fixed effects β k . In the NM, β 0 represented the expected average reading achievement of the reference group across cycles. The reference group represented the majority groups (born in Germany, both parents born in Germany, speaking German at home, more than 100 books at home, and no special educational needs) with average age and regular enrolment and without grade retention. The regression coefficient β cycle represented the reading achievement difference between the cycles if the students’ composition and the fixed effect β k of the student composition variables were the same in both cycles.

Third, the achievement gap model (AM) included an additional interaction between student composition and cycle. As in the other models, in the AM, β 0 represented the reading achievement of the reference group in 2016. β cycle represents the difference between the reference group in 2016 and 2021. The interaction effect represents the difference in the deviation between the reference group and the student subgroup in 2016 vs. 2021.

Descriptive Statistics

Descriptive statistics for reading achievement are reported in Implications: Research, Support, Educational Policy, Appendix A . The student composition changed statistically significantly between 2016 and 2021, with (a) a slightly higher relative cohort age in 2021 due to later test administration dates in 2021 ( t  = 14.13, p  < 0.001), (b) a higher percentage of children enrolled in school after turning age 6 ( t  = 2.59, p  = 0.009), (c) a higher percentage of students from immigrant backgrounds in terms of children who were themselves born abroad ( t  = 9.28, p  < 0.001), both of whose parents were not born in Germany ( t  = 3.59, p  < 0.001) and who did not speak German at home ( t  = 3.59, p  = 0.006), and (d) the percentage of students with special educational needs in general education schools ( t  = 2.01, p  = 0.044). There were no statistically significant differences in grade retention, gender distribution, one parent being born abroad, or number of books at home across the two study cycles in 2016 and 2021 (see details in Appendix A ).

Does Student Reading Achievement in 2021 Differ From Pre-COVID-19 Times in 2016?

The average reading achievement in 2021 was 980 points. In 2016, fourth graders from the same schools had a mean reading achievement of 1,000 points. The gross model (Model 1) describes the difference in reading achievement between the study cycles without taking into account changes in student composition (see Table 1 ), but including school random intercepts. The fixed effect for the difference between the study cycles was 19 points (β cycle  = −18.93, SE  = 3.04, p  < 0.001) for an average student in an average school. This difference of 19 points was statistically significant and corresponded to a standardized effect size of d  = 0.19 (note that the SD is 100). The slight deviation from the average score difference (20 points) results from controlling for the random intercept. In conclusion, on average, students’ reading achievement was lower in 2021 than in 2016. This result supported our Hypothesis 1.

Table 1 . Linear mixed-effect model explaining reading achievement.

Does Student Reading Achievement in 2021 Differ From Pre-COVID-19 Times in 2016 When Adjusting for Student Composition?

The net model (Model 2) displays the difference in reading achievement between 2016 and 2021 adjusted for student composition. The net model displayed a significant effect of study cycle β cycle  = −13.80, SE  = 3.03, p  < 0.001, indicating that the difference between 2016 and 2021 cannot fully be explained by the student composition variables. The corresponding effect size was d  = 0.14. This supports H2 that average reading achievement declined from 2016 to 2021 even when adjusting for student composition. The mean expected reading achievement for 2016 given the student composition in 2016 is 1,000 (i.e., mean for 2016), while the mean expected reading achievement for 2021 given the student composition in 2021 is 980 (i.e., mean for 2021). However, we can estimate the expected mean reading achievement for 2021 based on the student composition for 2016. The expected mean reading achievement for 2021 given the student composition for 2016 is 986, and thus, 14 points (i.e., d  = 0.14) lower than 2016.

In sum, these results indicate that the average reading achievement is lower in 2021 independently of student composition. This supports Hypothesis 2 that average reading achievement declined even when adjusting core characteristics of student composition.

Are There Achievement Gaps Between Subgroups of Students and Did They Change Over Time?

Table 2 shows the estimated subgroup differences in reading achievement, achievement gaps, and changes in achievement gaps. Overall, the results suggest that the achievement gap between students born in Germany and students born in other countries widened from 2016 to 2021. The gap between students with both parents born in Germany and students with both parents born abroad tend to be larger in 2021 than it was in 2016. Similarly, the gaps between students who primarily spoke German at home and students who did not primarily speak German at home tended to widen. There was no increase in the gender gap between 2016 and 2021. Lastly, the gap between children with one parent born in another country and children with both parents born in Germany and children with more and less than 100 books seemed to close. However, none of these differences was statistically significant.

Table 2 . Reading achievement gaps in different student subgroups.

The achievement gap model (Model 3) considers differential effects of the student composition variables. The model displays no significant interaction between the year and any of the student composition variables. This suggests that the achievement gaps in the student composition variables did not change significantly between 2016 and 2021. With respect to our hypotheses, we did find a gap between students with different socio-cultural capital, which is in accordance with H3.1.1. However, we did not find a widening gap between 2016 and 2021 (i.e., H3.1.2 was rejected). Furthermore, we found a gap between students from immigrant and non-immigrant backgrounds, which is in accordance with H3.2.1. However, we did not find a widening gap between 2016 and 2021 (i.e., H3.2.2 was rejected). Finally, we found a gender gap in reading achievement, which is in accordance with H3.3.1, but did not find a widening gap from 2016 to 2021 (i.e., H3.3.2 was rejected). In sum, none of the achievement gaps statistically significantly changed between 2016 and 2021.

The present work provided first empirical evidence on the status of reading achievement among German fourth graders after the COVID-19-related changes to schooling. Our study makes a cohort comparison of reading achievement among students from 111 elementary schools in Germany before the COVID-19 pandemic in 2016 and more than 1 year after the outbreak of the pandemic in 2021. We adjusted the results for student composition in both study cycles. In sum, there is clear evidence that reading achievement, a core learning outcome, is lower on average among current fourth graders compared to the pre-COVID-19 situation in 2016. The difference between 2016 and 2021 can only partially be explained by student composition. A difference of 19 points is way beyond changes in average reading achievement found in large-scale assessment over the past decades. Thus, it is likely that this decline in average reading achievement is at least partly due to COVID-19-related measures. The observed effects are in the range of the average impact of COVID-19-related school closures as reported in the meta-analysis by König and Frey (2022) ( d  = −0.18).

The observed decline in average reading achievement is remarkable. Baird and Pane (2019) discussed translating standardized effect sizes into years of learning to make them more interpretable. The average annual reading achievement gains in fourth grade are often considered d  = 0.40 with a margin of error of ±0.06 ( Hill et al., 2008 ). Thus, the decline of d  = −0.19 means that fourth graders in 2021 are around half a year of learning behind fourth graders in 2016. The decrease of d  = −0.14 when controlling for student composition would represent slightly more than 4 months of learning. Note that the effect size of annual literacy gains was not measured directly, and average annual literacy gains vary across studies (e.g., d  = 0.29: Ditton and Krüsken, 2009 ; d  = 0.48: Krüsken, 2007 ), so the half-year or 4-month learning time are not necessarily very precise estimates. Nonetheless, fourth graders in 2021 are substantially behind fourth graders in 2016, even with more conservative estimates. Hence, even though elementary schools implemented a variety of support measures during the COVID-19 pandemic ( Huber et al., 2020 ; Lorenz et al., 2020 ; Meinck et al., 2022 ), the results presented here support the concern that younger students were particularly affected by the pandemic schooling situation (see also Tomasik et al., 2020 ).

Contrary to expectations, we did not find statistically significant effects indicating widening achievement gaps between subgroups of students—here: socio-cultural capital, immigration background, and gender. However, the statistical power for such interaction effects is limited in our study. Our study considered different sources of statistical uncertainty, plausible value variance, sampling variance, and imputation variance, as well as weighting, which imposed a high standard on finding significant changes in achievement gaps. There are recent findings from the German federal state Baden-Württemberg based on an annual population survey suggesting that schools with a large proportion of students with migration background and with lower average socio-cultural capital, respectively, had larger average losses in achievement than other schools ( Schult et al., 2022 ). Therefore, it is likely that studies using larger samples or longitudinal designs can identify significant differences in achievement gaps. Thus, in light of the existing gaps and the low achievement levels of a substantial share of the student population, targeted support measures are clearly necessary. This finding is in line with previous studies (for Germany: Stanat et al., 2019 , internationally: Mullis et al., 2017 ).

Strengths and Limitations

There is a need for empirical evidence on the academic achievement of current student cohorts in order to understand how these students perform compared to their expected achievement in the absence of the COVID-19 pandemic. Our study is one of the first studies worldwide—and the first of its kind in Germany—to apply a rigorous methodology in order to estimate the actual status of students’ reading achievement in elementary schools. The presented analyses are based on a representative sample taking the standardized, well-established PIRLS reading achievement test. In contrast to other comparative studies, we present a school panel analysis. This has the main benefit of holding a number of key variables related to the educational environment, such as general school conditions (e.g., reading curricula) and school location, constant, allowing for a very high degree of comparability. Thus, the instrument and study design enable us to obtain reliable information on developments in achievement over time controlling for student composition as well as evidence on achievement gaps.

However, as a main limitation, it must be stated that no causal inferences on the effect of the containment measures during the COVID-19 pandemic on reading achievement since 2016 can be drawn. The prerequisites for causal inferences are not given. A control group is not available, since the COVID-19-related measures were applied to all schools, and our study is not longitudinal at the student level and therefore cannot control for pre-pandemic individual student characteristics. At least one of these two conditions (as well as a few others) would be necessary to estimate the causal effect of specific pandemic measures such as school closures of different lengths. In addition, there may be a slight underestimation of the full effect, as the measurement date in 2021 was on average 1 month later than in 2016.

Furthermore, we only investigated reading achievement as a comprehensive construct. However, reading is a multi-faceted construct ( Graesser and McNamara, 2011 ) with many contributing subprocesses such as word recognition (e.g., decoding skills), language comprehension (e.g., verbal reasoning), and bridging processes (e.g., vocabulary knowledge) and additionally, active self-regulation, motivation, and engagement ( Duke and Cartwright, 2021 ). All of these subprocesses could be influenced by the COVID-19 pandemic conditions. Further insights into which particular reading subprocesses were especially impaired could help to further improve post-COVID-19 reading interventions. We will have to leave this to further research, as the panel study was not originally designed to allow for these in-depth analyses.

Implications: Research, Support, and Educational Policy

However, the presented findings lead to important conclusions regarding further research, educational practice, and educational policy. Further analyses may provide more in-depth insights. These include differentially considering reading achievement for literary texts compared with informational texts, which may lead to more gender-specific findings, as girls’ performance advantages at the end of fourth grade are especially prominent for literary texts ( Mullis et al., 2017 ), and this may have been further reinforced by increased reading for pleasure during the COVID-19 pandemic-related restrictions. In addition, it should be examined whether the results also apply to other domains such as mathematics or to older groups of students. Finally, international comparisons are urgently needed to clarify whether the pattern found for Germany holds for other countries as well. This will be possible in the future using data from internationally comparative school achievement surveys such as PIRLS 2021 (elementary school, to be published in December 2022) and PISA 2022 (secondary schools, assessed in 2022). Similarly, national large-scale assessments of student achievement can also be insightful ( Stanat et al., 2019 ) and could help to refine our findings in the future.

Regarding educational practice, it should be noted that compensatory measures have not been sufficiently effective for elementary school students in Germany more than a year after the onset of the COVID-19 pandemic-related restrictions on school operations but since then comprehensive measures have started to take place in Germany. Indeed, the findings highlight the need for comprehensive support—for all learners, as shown by the overall effect, but also targeted support for specific groups of students, as illustrated by the significant achievement gaps at the end of fourth grade, even if these were not further amplified compared to 2016. Here, coordinated targeted support approaches must be used that focus on systematically support reading skills in the classroom, extracurricular support during students’ leisure time, and during school vacations, as well as support from the family. Lastly, we assessed reading achievement shortly before most students in Germany transition to secondary schools. Therefore, the study provides information that could help secondary school teachers better understand the needs of rising fifth graders in post-COVID-19 times.

The findings are also informative for the design of educational policy. It should be concluded that the framework and conditions for learning in crisis situations need to be strengthened. This includes but is not limited to expanding the framework conditions and use of digital media, but also promoting resilience at all levels (i.e., among learners and their families, teachers, schools, and the educational system). Furthermore, self-regulated learning should be fostered among students of all ages, and last but not least, reading skills should be effectively supported at an early stage, as a key competency for all learners that enables them to acquire learning content relatively independently even in extraordinary learning situations such as distance learning.

The aim of the present study was to gain profound insights into the status of students’ achievement in the key competence of reading after a long period of COVID-19-related restrictions on learning at school and to identify any necessary support needs. In conclusion, society, as well as educational practice and educational policy more specifically, are now tasked with implementing effective supports for the children and adolescents affected by the COVID-19 pandemic in order to effectively secure their educational and life chances.

Data Availability Statement

The datasets presented in this article are not readily available because publication restrictions apply until the end of 2022. When available, the datasets will be available here: https://www.fdz-bildung.de/home .

Ethics Statement

Ethical review and approval was not required for the current study in accordance with the local legislation and institutional requirements. Written informed consent was not required in accordance with the national legislation and the institutional requirements. The original studies that led to the creation of the dataset were reviewed and approved by the Ministers of Education (“Kultusminister der Länder”) of all 16 federal states in Germany, and written informed consent to participate in these studies was provided by the participants’ legal guardian/next of kin.

Author’s Note

Content, ethical aspects, and data protection have been thoroughly examined by the responsible (data protection) officers of each of the 16 German federal states.

Author Contributions

NM and RL contributed to the conception and design of the study. UL prepared the database, performed the statistical analysis, and wrote the first draft of the method and result section. NM wrote the first draft of introduction and discussion. TS, RS, and RK wrote paragraphs of the manuscript. UL, NM, RL, TS, RS, RK, CK, and AF contributed to manuscript revision, read, and approved the submitted version. All authors contributed to the article and approved the submitted version.

The study was funded by the Federal Ministry of Education and Research (BMBF) and the Standing Conference of the Ministers of Education and Cultural Affairs of the German federal states (KMK).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We would like to thank our intern Carina Jüschke for her support in the preparation of this manuscript and Sebastian Weirich, Matthias Trendtel, and Jakob Schwerter for their advice on methodological implementation. In addition, we would like to thank Keri Hartmann for proofreading of an earlier version of this manuscript.

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Wrase, M. (2020). “Schulrechtliche Herausforderungen in Zeiten der Corona-Pandemie [School law challenges in times of the Corona pandemic],” in “Langsam vermisse ich die Schule…” – Schule während und nach der Corona-Pandemie . eds. D. Fickermann and B. Edelstein (Münster, Germany: Waxmann), 105–116.

Zierer, K. (2021). Effects of pandemic-related school closures on pupils’ performance and learning in selected countries: a rapid review. Educ. Sci. 11:252. doi: 10.3390/educsci11060252

Descriptive results comparing the student composition in 2016 and 2021.

Keywords: reading comprehension, reading achievement, COVID-19, elementary school, achievement gaps, large-scale assessment

Citation: Ludewig U, Kleinkorres R, Schaufelberger R, Schlitter T, Lorenz R, König C, Frey A and McElvany N (2022) COVID-19 Pandemic and Student Reading Achievement: Findings From a School Panel Study. Front. Psychol . 13:876485. doi: 10.3389/fpsyg.2022.876485

Received: 15 February 2022; Accepted: 01 April 2022; Published: 18 May 2022.

Reviewed by:

Copyright © 2022 Ludewig, Kleinkorres, Schaufelberger, Schlitter, Lorenz, König, Frey and McElvany. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ulrich Ludewig, [email protected]

† ORCID: Ulrich Ludewig, orcid.org/0000-0001-9614-847X Ruben Kleinkorres, orcid.org/0000-0002-9689-8796 Rahim Schaufelberger, orcid.org/0000-0003-4489-6761 Theresa Schlitter, orcid.org/0000-0001-5269-0451 Ramona Lorenz, orcid.org/0000-0002-5733-5421 Christoph König, orcid.org/0000-0003-3172-7029 Andreas Frey, orcid.org/0000-0001-5334-9538 Nele McElvany, orcid.org/0000-0001-8649-5523

This article is part of the Research Topic

Mind the Gap: To What Extent Do Social, Economic, and Psychological Factors Explain Underperformance in Achievements Assessments? Identifying Interventions to Narrow the Gap

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• Editor's Pick

Harvard Students Report Surge in Covid-19 Cases with Fall Semester Underway

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Most freshmen arrive at Harvard College eager to participate in orientation activities, from wilderness hikes to leadership training. But this fall, some spent their first few days on campus in isolation amid a spike in Covid-19 infections.

Covid-19 cases and hospitalizations have been on the rise in the Greater Boston area since mid-July. But even as Harvard has slashed its Covid-19 restrictions , students said the virus has continued to have a disruptive effect on the beginning of the fall semester.

Harvard University Health Services Executive Director Giang T. Nguyen shared Covid-19 guidance with affiliates in an Aug. 25 email, encouraging them to take a rapid test before arrival on campus and follow CDC guidelines, which dictate isolating for five days after a positive test. According to Nguyen’s email, students can attend class if they test negative after exposure to Covid-19.

In a subsequent email sent to students and residential staff on Aug. 31, Associate Dean of Students Lauren E. Brandt ’01 wrote that Covid-19 tests would be “distributed upon individual request 1 at a time until the supply is exhausted” from house building manager offices.

Umaama Hussain ’27 tested positive at the start of freshman orientation, and she said the tight conditions in her room made it difficult to socially distance.

“I kept my door locked, and every time I left my room I put on a mask, but we’d obviously run into each other sharing the same common space and the bathroom,“ Hussain said. “So that was a bit tough.”

After testing positive for Covid-19, Hussain contacted her proctor, who sent her a list of instructions regarding self-isolation. Though Hussain said she found Harvard’s response to Covid-19 sufficient overall with guidelines that were “pretty clear cut,” she said it was difficult to obtain necessities while self-isolating.

“I wish there had been a bit more support in terms of just getting food and essentials to the dorm,” Hussain said.

Mirika Jambudi ’27, whose suitemate tested positive for Covid-19 early in the year, also reported difficulty social distancing in her dorm.

“In Wigg, the rooms are super small, so there’s not much I can do to avoid suitemate contact, and Harvard has no procedure for what to do with that,” Jambudi said.

In response to student criticisms of Harvard’s response, HUHS spokesperson Tiffanie A. Green pointed to Nguyen’s Aug. 25 email.

“COVID-19 continues to circulate both locally and nationally. Harvard University Health Services urges members of the community to adhere to the precautions detailed in the Fall semester public health message to protect themselves and others,” Green wrote.

Elizabeth S. Pollard ’27 was one of several students to test positive after participating in the First-Year Retreat Experience pre-orientation program. Testing positive during orientation meant Pollard was unable to take part in many events, including field day and First Chance Dance.

“I feel like I was able to adjust pretty well and pick up on everything,” Pollard said. “But it was definitely unfortunate to have to miss out on all of those activities.”

Mower Hall resident Chanden A. Climaco ’27, who tested positive at the start of the semester, said he believes Harvard’s current guidelines are enough to prevent the spread of Covid-19 “as long as people are adhering to them.”

“I haven’t looked at Covid guidelines in a while,” Climaco said. “It seems like this resurgence has been one of the first times I’m actually hearing of Covid in several months, and so looking at what the policies were and seeing that they weren’t two weeks of quarantine that will be enforced was maybe a little surprising, but I don’t have a take on whether it was good or bad necessarily.”

Jack A. Kelly ’26, who tested positive for Covid-19 last week, said he feels a “little bit of frustration” over how administrators and faculty have handled the fall uptick.

“I felt like there weren’t super well-defined Covid policies, that when I was talking with professors, it almost felt like I was asking for special treatment,” Kelly said. “You should never feel like you’re asking for special treatment — you're just asking for it to be recognized that you have Covid, that you’re going to be a little bit behind, and that you’re going to need some support catching up.”

—Staff writer Alexander I. Fung can be reached at [email protected] .

—Staff writer Tarah D. Gilles can be reached at [email protected] .

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More students gain eligibility for free school meals under expanded US program

WASHINGTON (AP) — Millions of additional students in schools serving low-income communities will be eligible to receive breakfast and lunch at no cost under a rule change announced Tuesday by the U.S. Department of Agriculture.

At schools where 25% of families participate in income-based public benefits, such as the Supplemental Nutritional Assistance Program, the federal government now will cover the cost of free meals for all enrolled students. Previously, the qualifying threshold was 40%.

Roughly 3,000 additional school districts serving more than 5 million students will now be eligible, officials said.

“While there is still more work ahead to ensure every K-12 student in the nation can access healthy school meals at no cost, this is a significant step on the pathway toward that goal,” said Stacy Dean, USDA deputy under secretary for Food, Nutrition, and Consumer Services.

During the pandemic, Congress temporarily made  universal meals free to all students , but that ended last year. Other federal programs that provided direct food assistance to families also scaled down amid soaring food prices, putting strains on family budgets and  leaving some kids hungry .

Meantime, eight states — California, Colorado, Maine, Massachusetts, Michigan, Minnesota, New Mexico and Vermont — have made school meals  free to all  students regardless of income.

The new rule will expand access to universal meals through a program known as the Community Eligibility Provision, or CEP. Instead of requiring families to fill out individual applications for free or reduced-price meals, schools participating in the program receive federal funding based on income data, with local or state money filling in any gaps in the cost of offering meals to all students. Advocates say reducing administrative burdens like applications helps ensure children don’t go hungry.

Some have criticized the costs of the program. The Republican Study Committee has called for  eliminating the CEP altogether , arguing it ignores the individual income eligibility of each student.

Nationally, expanding a community-based model of universal meals would alleviate burdens on many families, said Anna Korsen, policy and program director at Full Plates Full Potential, a nonprofit organization in Maine that works on maximizing access to school meals.

“The federal poverty guidelines that dictate who gets a free meal and who doesn’t are really outdated,” Korsen said. “There are so many families that on paper don’t qualify for a free meal, and they can get lumped into this group of ... families that can afford to pay for lunch or breakfast at school. But really, those families are living paycheck to paycheck.”

Agriculture secretary Tom Vilsack said the rule change is a step toward fulfilling the promise of healthy school meals for all.

“Increasing access to free, healthy school breakfast and lunch will decrease childhood hunger, improve child health and student readiness, and put our nation on the path to better nutrition and wellness,” he said.

The Associated Press education team receives support from the Carnegie Corporation of New York. The AP is solely responsible for all content.

Copyright 2023 The Associated Press. All rights reserved.

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Biden cancels $37 million in student loan debt for former university of phoenix students.

The Biden administration is canceling nearly $37 million of federal student loan debt for more than 1,200 borrowers who attended the University of Phoenix because it found that the for-profit school misled students about job prospects.

Taking a narrower approach to student debt forgiveness, the Biden administration has continued to cancel some borrowers’ debts under existing programs after the Supreme Court blocked its broad student loan forgiveness program that promised to forgive up to $20,000 for low- and middle-income borrowers.

Similar to Wednesday’s announcement about the University of Phoenix, the Department of Education canceled $72 million in federal student loan debt in August for more than 2,300 borrowers who attended the for-profit Ashford University in California.

Altogether, the administration has canceled more than $117 billion of the nearly $1.7 trillion of outstanding federal student loan debt since 2021.

The former University of Phoenix students now eligible for debt relief were enrolled at the school between September 21, 2012, and December 31, 2014, and have already applied for loan forgiveness under a program called borrower defense to repayment. The program has been in place for decades and allows people to apply for debt relief if they believe their college misled or defrauded them.

Are you ready to start repaying your student loans?

Building on an investigation by the Federal Trade Commission, the Department of Education found that the University of Phoenix falsely represented that its partnerships with thousands of corporations, including Fortune 500 companies, would give students hiring preferences.

In 2019, the FTC reached a settlement agreement with the University of Phoenix over similar claims. The company did not admit to or deny any allegations at that time.

“The University of Phoenix brazenly deceived prospective students with false ads to get them to enroll,” said Federal Student Aid chief operating officer Richard Cordray in a statement.

“Students who trusted the school and wanted to better their lives through education ended up with mounds of debt and useless degrees,” he added.

In a statement sent to CNN Wednesday, the University of Phoenix refuted the government’s findings and noted that the school admitted no wrongdoing when settling with the FTC in 2019.

“We respectfully, but adamantly disagree with the U.S. Department of Education’s allegations related to the Dec. 2019 University of Phoenix settlement with the Federal Trade Commission,” it said.

“While the University is not against relief for borrowers who have valid claims, we intend to vigorously challenge each frivolous allegation and suspicious claim through every available legal avenue,” it added.

The Department of Education said it will notify eligible borrowers by early October that their debt relief applications have been approved. The government will instruct student loan servicers to put affected borrowers’ loans in forbearance until the debt is officially canceled.

Borrowers whose loans are in forbearance won’t be required to make payments, even after the pandemic-related freeze on federal student loan payments ends in October .

Other former University of Phoenix students who believe they were similarly affected during those years can still apply for student debt relief under the borrower defense program at the Federal Student Aid website.

The Biden administration has made it easier for borrowers to apply for federal student loan forgiveness from a variety of existing programs. It expanded eligibility for the Public Service Loan Forgiveness program, which wipes away outstanding debt for public sector workers after they make 10 years of qualifying payments, and is conducting a one-time account adjustment that will result in the cancellation of debt for borrowers who have been paying for at least 20 years.

In August, the administration also launched a new income-driven repayment plan, known as SAVE (Saving on a Valuable Education) , which will reduce monthly payments and the amount paid back over time for eligible student loan borrowers.

This story has been updated with additional information.