a literature review map

• Research Guides

Literature Review: A Self-Guided Tutorial

Using concept maps.

• Literature Reviews: A Recap
• Peer Review
• Reading the Literature
• Developing Research Questions
• Considering Strong Opinions
• 2. Review discipline styles
• Super Searching
• Finding the Full Text
• Citation Searching This link opens in a new window
• When to stop searching
• Citation Management
• Annotating Articles Tip
• 5. Critically analyze and evaluate
• How to Review the Literature
• Using a Synthesis Matrix
• 7. Write literature review

Concept maps or mind maps visually represent relationships of different concepts. In research, they can help you make connections between ideas. You can use them as you are formulating your research question, as you are reading a complex text, and when you are creating a literature review. See the video and examples below.

How to Create a Concept Map

Credit: Penn State Libraries ( CC-BY ) Run Time: 3:13

• Bubbl.us Free version allows 3 mind maps, image export, and sharing.
• MindMeister Free version allows 3 mind maps, sharing, collaborating, and importing. No image-based exporting.

Mind Map of a Text Example

Credit: Austin Kleon. A map I drew of John Berger’s Ways of Seeing in 2008. Tumblr post. April 14, 2016. http://tumblr.austinkleon.com/post/142802684061#notes

Literature Review Mind Map Example

This example shows the different aspects of the author's literature review with citations to scholars who have written about those aspects.

Credit: Clancy Ratliff, Dissertation: Literature Review. Culturecat: Rhetoric and Feminism [blog]. 2 October 2005. http://culturecat.net/node/955 .

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• Last Updated: Jun 28, 2023 12:04 PM
• URL: https://libguides.williams.edu/literature-review

How to Master at Literature Mapping: 5 Most Recommended Tools to Use

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After putting in a lot of thought, time, and effort, you’ve finally selected a research topic . As the first step towards conducting a successful and impactful research is completed, what follows it is the gruesome process of literature review . Despite the brainstorming, the struggle of understanding how much literature is enough for your research paper or thesis is very much real. Unlike the old days of flipping through pages for hours in a library, literature has come easy to us due to its availability on the internet through Open Access journals and other publishing platforms. This ubiquity has made it even more difficult to cover only significant data! Nevertheless, an ultimate solution to this problem of conglomerating relevant data is literature mapping .

Table of Contents

What is Literature Mapping?

Literature mapping is one of the key strategies when searching literature for your research. Since writing a literature review requires following a systematic method to identify, evaluate, and interpret the work of other researchers, academics, and practitioners from the same research field, creating a literature map proves beneficial. Mapping ideas, arguments, and concepts in a literature is an imperative part of literature review. Additionally, it is stated as an established method for externalizing knowledge and thinking processes. A map of literature is a “graphical plan”, “diagrammatic representation”, or a “geographical metaphor” of the research topic.

Researchers are often overwhelmed by the large amount of information they encounter and have difficulty identifying and organizing information in the context of their research. It is recommended that experts in their fields develop knowledge structures that are richer not only in terms of knowledge, but also in terms of the links between this knowledge. This knowledge linking process is termed as literature mapping .

How Literature Mapping Helps Researchers?

Literature mapping helps researchers in following ways:

• It provides concrete evidence of a student’s understanding and interpretation of the research field to share with both peers and professors.
• Switching to another modality helps researchers form patterns to see what might otherwise be hidden in the research area.
• Furthermore, it helps in identifying gaps in pertinent research.
• Finally, t lets researchers identify potential original areas of study and parameters of their work.

How to Make a Literature Map?

Literature mapping is not only an organizational tool, but also a reflexive tool. Furthermore, it distinguishes between declarative knowledge shown by identifying key concepts, ideas and methods, and procedural knowledge shown through classifying these key concepts and establishing links or relationships between them. The literature review conceptualizes research structures as a “knowledge production domain” that defines a productive and ongoing constructive element. Thus, the approaches emphasize the identity of different scientific institutions from different fields, which can be mapped theoretically, methodologically, or fundamentally.

The two literature mapping approaches are:

• Mapping with key ideas or descriptors: This is developed from keywords in research topics.
• Author mapping: This is also termed as citation matching that identifies key experts in the field and may include the use of citations to interlink them.

Generally, literature maps can be subdivided by categorization processes based on theories, definitions, or chronology, and cross-reference between the two types of mapping. Furthermore, researchers use mind maps as a deductive process, general concept-specific mapping (results in a right triangle), or an inductive process mapping to specific concepts (results in an inverted triangle).

What are Different Literature Mapping Methods?

The different types of literature mapping and representations are as follows:

1. Feature Mapping:

Argument structures developed from summary registration pages.

2. Topic Tree Mapping:

Summary maps showing the development of the topic in sub-themes up to any number of levels.

3. Content Mapping:

Linear structure of organization of content through hierarchical classification.

4. Taxonomic Mapping:

Classification through standardized taxonomies.

5. Concept Mapping:

Linking concepts and processes allows procedural knowledge from declarative information. With a basic principle of cause and effect and problem solving, concept maps can show the relationship between theory and practice.

6. Rhetorical Mapping:

The use of rhetoric communication to discuss, influence, or persuade is particularly important in social policy and political science and can be considered a linking strategy. A number of rhetorical tools have been identified that can be used to present a case, including ethos, metaphor, trope, and irony.

7. Citation Mapping:

Citation mapping or matching is a research process established to specifically establish links between authors by citing their articles. Traditional manual citation indexes have been replaced by automated databases that allow visual mapping methods (e.g. ISI Web of Science). In conclusion, citation matching in a subject area can be effective in determining the frequency of authors and specific articles.

5 Most Useful Literature Mapping Tools

Technology has made the literature mapping process easier now. However, with numerous options available online, it does get difficult for researchers to select one tool that is efficient. These tools are built behind explicit metadata and citations when coupled with some new machine learning techniques. Here are the most recommended literature mapping tools to choose from:

1. Connected Papers

a. Connected Papers is a simple, yet powerful, one-stop visualization tool that uses a single starter article.

b. It is easy to use tool that quickly identifies similar papers with just one “Seed paper” (a relevant paper).

c. Furthermore, it helps to detect seminal papers as well as review papers.

d. It creates a similarity graph not a citation graph and connecting lines (based on the similarity metric).

e. Does not necessarily show direct citation relationships.

f. The identified papers can then be exported into most reference managers like Zotero, EndNote, Mendeley, etc.

2. Inciteful

a. Inciteful is a customizable tool that can be used with multiple starter articles in an iterative process.

b. Results from multiple seed papers can be imported in a batch with a BibTex file.

c. Inciteful produces the following lists of papers by default:

• Similar papers (uses Adamic/Adar index)
• “Most Important Papers in the Graph” (based on PageRank)
• Recent Papers by the Top 100 Authors
• The Most Important Recent Papers

d. It allows filtration of results by keywords.

e. Importantly, seed papers can also be directly added by title or DOI.

a. Litmaps follows an iterative process and creates visualizations for found papers.

b. It allows importing of papers using BibTex format which can be exported from most reference managers like Zotero, EndNote, Mendeley. In addition, it allows paper imports from an ORCID profile.

c. Keywords search method is used to find Litmaps indexed papers.

d. Additionally, it allows setting up email updates of “emergent literature”.

e. Its unique feature that allows overlay of different maps helps to look for overlaps of papers.

f. Lastly, its explore function allows finding related papers to add to the map.

4. Citation-based Sites

a. CoCites is a citation-based method for researching scientific literature.

b. Citation Gecko is a tool for visualizing links between articles.

c. VOSviewer is a software tool for creating and visualizing bibliometric networks. These networks are for example journals, may include researchers or individual publications, which can be generated based on citation, bibliographic matching , co-citation, or co-authorship relationships. VOSviewer also offers text mining functionality that can be used to create and visualize networks of important terms extracted from a scientific literature.

5. Citation Context Tools

a. Scite allow users to see how a publication has been cited by providing the context of the citation and a classification describing whether it provides supporting or contrasting evidence for the cited claim.

b. Semantic Scholar is a freely available, AI-powered research tool for scientific literature.

Have you ever mapped your literature? Did you use any of these tools before? Lastly, what are the strategies and methods you use for literature mapping ? Let us know how this article helped you in creating a hassle-free and comprehensive literature map.

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Writing a Literature Review

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

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You are here, structuring your ideas: creating a literature map.

It is important to have a plan of the areas to be discussed, using this to indicated how these will link together. In the overall structure of the literature review, there should be a logical flow of ideas and within each paragraph there should be a clear theme, around which related ideas are explored and developed. A literature map can be useful for this purpose as it enables you to create a visual representation of the themes and how they could relate to one another.

A literature map (Cresswell, 2011) is a two dimensional diagrammatic representation of information where links are made between concepts by drawing arrows (which could be annotated to define the nature of these links). Constructing a literature map helps you to:

• develop your understanding of the key issues and research findings in the literature
• to organise ideas in your mind
• to see more clearly how different research studies relate to one another and to group those with similar findings.

Your map can then be used as a plan for your literature review.

As well has helping you to organise the literature for your review, a literature map can be used to help you analyse the information in a particular journal article, supporting the exploration of strengths and weaknesses of the methodology and the resultant findings and enabling you to explore how key themes and concepts in the article link together.

It is important to represent the different views and any conflicting research findings that exist in the literature (Newby, 2014). There is a danger of selective referencing, only including literature that supports your own beliefs and findings, disregarding alternative views. This should be avoided as it is based on the assumption that your views are the correct ones, and it is possible that you could miss key ideas and findings that could take your research in new and exciting directions.

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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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Literature Reviews

• What is a Literature Review?
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Concept map example: Chocolate Purchasing Factors

What is concept mapping.

Concept Maps are a way to graphically represent ideas and how they relate to each other.

Concept maps may be simple designs illustrating a central theme and a few associated topics or complex structures that delineate hierarchical or multiple relationships.

J.D. Novak developed concept maps in the 1970's to help facilitate the research process for his students. Novak found that visually representing thoughts helped students freely associate ideas without being blocked or intimidated by recording them in a traditional written format.

Concept mapping involves defining a topic; adding related topics; and linking related ideas

Use Bubbl.us or search for more free mind-mapping tools on the web.

More Examples of Concept Maps

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Literature Review: The What, Why and How-to Guide — How to Pick a Topic

• Getting Started
• Introduction
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Picking a Topic and Keywords to Research your Topic

Whether you are writing a literature review as a standalone work or as part of a paper, choosing a topic is an important part of the process. If you haven't select a topic yet for your literature view or you feel that your topic is too broad, this page is for you!

The key to successfully choosing a topic is to find one that is not too broad (impossible to adequately cover) but also not too narrow (not enough has been written about it). Use the tools below to help you brainstorm a topic and keywords that then you can use to search our many databases. Feel free to explore these different options or  contact a Subject Specialist if you need more help!

Concept Mapping

• [REMOVE] Mind Mapping (also known as Concept Mapping) A helpful handout to show step by step how to create a concept map to map out a topic.

Picking a topic and search terms

Below are some useful links and handouts that help you develop your topic. Check the handouts in this page. They are useful to help you develop keywords/search terms or to learn the best way to search databases to find articles and books for your research.

• UVA Thinking Tool: Choosing a Topic and Search Terms Provides a template for focusing a research assignment through the brainstorming of ideas, keywords, and other terminology related to a topic.
• UW How to Improve Database Search Results Suggested strategies for retrieving relevant search results
• UCLA: Narrowing a Topic Useful tips on how to narrow a topic when you are getting too many results in your search. From the librarians at UCLA.
• UCLA: Broadering a Topic Useful tips on how to broaden your topic when you are getting few results in your search. From the librarians at UCLA.
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Literature mapping.

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What is Literature Mapping?

Literature mapping is a way of discovering scholarly articles by exploring connections between publications.

Similar articles are often linked by citations, authors, funders, keywords, and other metadata. These connections can be explored manually in a database such as Scopus or by the use of free browser-based tools such as Connected Papers , L itMaps , and Open Knowledge Maps . 

The following is an introduction to these four methods. 

Video Tutorial (24min)

Literature mapping in 30 minutes (slides).

• Literature Mapping in 30 Minutes Fall 2023 (slides)
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Literature Review Map Template

Editable literature review map template to visualize the connections and associations between things. Organize your ideas

You can easily edit this template using Creately's mind mapping software . You can export it in multiple formats like JPEG, PNG and SVG and easily add it to Word documents, Powerpoint (PPT) presentations, Excel or any other documents. You can export it as a PDF for high-quality printouts.

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Literature review toolkit for policy studies: Concept mapping

Why create a concept map.

A concept map is a visualization of key idea in your research and the relationships between them. To create a concept map, pick out the main concepts of your topic and brainstorm everything you know about them, drawing shapes around your concepts and clustering the shapes in a way that's meaningful to you. How can this help?

• Helps you pull back to see the broader concepts at play.
• Can help identify the subject-based tool where literature can be found. 
• Helps clarify both what you already know and where you have gaps in your knowledge.

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Cantrell A, Croot E, Johnson M, et al. Access to primary and community health-care services for people 16 years and over with intellectual disabilities: a mapping and targeted systematic review. Southampton (UK): NIHR Journals Library; 2020 Jan. (Health Services and Delivery Research, No. 8.5.)

Access to primary and community health-care services for people 16 years and over with intellectual disabilities: a mapping and targeted systematic review.

Chapter 2 the mapping review methods.

A systematic mapping review was undertaken to map the literature in the topic area and to help decide on the final scope for the targeted systematic review.

The mapping review aimed to examine the volume and characteristics of the available evidence about quality of access to primary health-care services for people with ID. The protocol for the mapping review is provided in Report Supplementary Material 1 .

The mapping review includes the following types of health service:

• NHS primary care
• first-point community-based services [general practitioners (GPs), pharmacists, dentists and optometrists]
• sexual health
• health screening delivered in the context of primary and community care
• palliative and end-of-life care delivered in the context of primary care.
• Research questions
• What are the gaps in evidence about access to primary and community health care for people with ID?
• What are the barriers to accessing primary and community health-care services for people with ID and their carers?
• What actions, interventions or models of service provision improve access to health services for people with ID and their carers?

The systematic mapping review was conducted in accordance with published methods. 23 The mapping review followed the scope of a previous review, 21 , 24 with the exception that it focused on only primary and community care services.

We chose to build on the existing review for four compelling reasons:

• We could follow (and hopefully enhance) the methods of the original review.
• The time that had elapsed since the original work (approximately 15 years) provided a manageable quantity of literature for logistic purposes.
• The conceptual framework produced by the original team could be used as a template for data extraction if appropriate.
• Our updated review would follow seamlessly from the original work.

Areas of research activity and research gaps identified in the mapping review helped inform and finalise the scope for the targeted systematic review.

• Literature search for the mapping review

The literature search was informed by methods of identifying the literature described by McNally and Alborz. 25

We searched the following databases (seven of the 14 bibliographic databases in the Alborz et al. review 21 ):

• MEDLINE (via Ovid, 1946 to 2018)
• Science Citation Index Expanded; Social Sciences Citation Index (via Web of Science, 1900 to 2018)
• Cochrane Database of Systematic Reviews (1996 to 2018)
• Database of Abstracts of Reviews of Effect (1995 to 2015)
• Cochrane Central Register of Controlled Trials (1898 to 2018)
• Health Technology Assessment Database (1995 to 2016)
• NHS Economic Evaluations Database (1995 to 2015)
• Cumulative Index to Nursing and Allied Health (via EBSCO host 1974 to 2018)
• Applied Social Science Index (via ProQuest, 1987 to 2018)
• PsycINFO (via Ovid, 1806 to 2018)
• Educational Resources Index (via ProQuest, 1966 to 2018).

The database search strategy was adapted from methods described in the existing review for identifying the literature. 25 The search strategy comprised key terms for ID and access. Additional terminology was added to include the primary care setting (e.g. GPs, dentists, optometrists) and recent or current legislation or guidance terms, such as the Disability Discrimination Act and ‘reasonable adjustments’. The existing review was conducted between 1980 and 2002 so this search was limited from 1 January 2002 onwards, thereby ensuring continuity of the evidence base. The search was also restricted to English-language and human studies. The search strategy is provided in Appendix 1 .

Supplementary searching included grey literature searching of the websites of key UK charities and associations to identify reports about initiatives to improve access to services for people with ID. Snowballing by citation searching key studies was also performed in Google Scholar™ (Google Inc., Mountain View, CA, USA) and reference lists of included papers were scrutinised.

Study screening and selection was undertaken in EPPI-Reviewer 4 (Evidence for Policy and Practice Information and Co-ordinating Centre, University of London, London, UK). A team of three reviewers screened the identified references. An initial 100 references were screened by all three reviewers to check for consistency. Any queries were resolved through discussion with the other two reviewers.

Study selection was undertaken according to the inclusion criteria outlined in Table 1 .

Study selection criteria

Following screening at the title and abstract stage, the references that potentially met the inclusion criteria were considered further, and data were extracted for inclusion in the review. Citations not meeting the inclusion criteria were excluded.

• Data extraction

Data extraction based on abstracts was undertaken in EPPI-Reviewer 4 using a template designed for the mapping review (see Appendix 2 ). Mapping at the abstract level is a typical component of systematic mapping review methodology, given that the primary purpose is to plan a subsequent review. The extraction form comprised the following items: paper identifying code, author, date, study design, setting – country, health-care professional (HCP), specialist topic, study population, sample size, needs assessment, study outcomes, tools used to measure outcomes, study result, and barriers and facilitators. For mapping purposes, references were categorised into sets according to HCP or specialist topic, and ‘needs assessment’ papers were also considered as a separate categorisation. Data extraction was completed using data included in each abstract. If the abstract was unavailable, brief details were extracted from the title for the mapping review on the understanding that the full text would be obtained if included in the targeted systematic review. An example of a completed data extraction table is in Appendix 3 .

• Patient and public involvement

During the mapping review, we consulted people with ID, family carers and formal paid carers so that the review of access to health care for people with ID could be informed by the views and experiences of stakeholders. The aim of this consultation was to:

• illuminate the model of access to health care for people with ID
• inform and refine our search strategies by identifying barriers to accessing health care and any solutions developed
• identify gaps in the literature.

We contacted the clinical director and senior commissioning manager for services for people with ID in a Clinical Commissioning Group and asked them to identify relevant community groups for people with ID and their carers. We sent information about the review to these groups and asked to visit to discuss their experiences of accessing health care.

We met a group of people with ID ( n  = 8, plus one personal assistant) and a group of family carers ( n  = 5). Snowball sampling was used to identify formal carers and we spoke to staff who manage support services ( n  = 2). These were convenience samples depending on who attended the group or meeting on the day we visited.

Discussions were loosely guided by a topic guide covering how people identify a health need, what actions they take, the issues influencing their decision to take a particular course of action and the barriers to and facilitators of their access and use of the chosen service. 21 Notes were taken during each meeting and these were written up afterwards using bullet points to document the barriers and facilitators. These were organised under the headings ‘identifying and communicating symptoms of ill health’, ‘arranging and attending health appointments’ and ‘continuing access to services’. A brief summary is provided in Table 2 .

Patient and public involvement discussions

The barriers and facilitators were used to identify relevant search terms and for future comparison with the barriers and facilitators identified in the qualitative literature.

Detailed notes from the patient and public involvement (PPI) meetings are provided in Appendix 4 .

We plan to present our findings following completion of the targeted review with the pre-existing groups of people with ID, and their paid and unpaid carers. Comments on the Plain English summary were received from the facilitator of the pre-existing group of people with ID.

We have continued to involve patients and members of the public through the Sheffield Evidence Synthesis Centre PPI group. Members of this group were asked to comment on the scope of the targeted systematic review.

• Cite this Page Cantrell A, Croot E, Johnson M, et al. Access to primary and community health-care services for people 16 years and over with intellectual disabilities: a mapping and targeted systematic review. Southampton (UK): NIHR Journals Library; 2020 Jan. (Health Services and Delivery Research, No. 8.5.) Chapter 2, The mapping review methods.
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A literature review of open-ended concept maps as a research instrument to study knowledge and learning

• Open access
• Published: 24 February 2021
• volume  56 ,  pages 73–107 ( 2022 )

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• Kirsten E. de Ries   ORCID: orcid.org/0000-0002-6210-5604 1 ,
• Harmen Schaap 2 ,
• Anne-Marieke M. J. A. P. van Loon 1 ,
• Marijke M. H. Kral 1 &
• Paulien C. Meijer 2  

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Cite this article

In educational, social or organizational studies, open-ended concept maps are used as an instrument to collect data about and analyze individuals’ conceptual knowledge. Open-ended concept map studies devoted to knowledge and learning apply a variety of methods of analysis. This literature review systematically summarizes the various ways in which open-ended concept maps have been applied in previous studies of knowledge and learning. This paper describes three major aspects of these studies: what methods of analysis were used, what concept map characteristics were considered, and what conclusions about individuals’ knowledge or understanding were drawn. Twenty-five studies that used open-ended concept maps as a research instrument were found eligible for inclusion. In addition, the paper examines associations between the three aspects of the studies and provides guidelines for methodological coherence in the process of such analysis. This review underscores the importance of expatiating on choices made concerning these aspects. The transparency provided by this method of working will contribute to the imitable application of open-ended concept maps as a research tool and foster more informed choices in future open-ended concept map studies.”

Avoid common mistakes on your manuscript.

1 Introduction

Concept maps were introduced by Novak and Gowin to activate or elaborate (prior) knowledge. “Concept maps are graphical tools for organizing and representing knowledge. They include concepts, usually enclosed in circles or boxes of some type, and relationships between concepts indicated by a connecting line linking two concepts” (Novak and Cañas 2008 , p.1). Concept maps have a wide variety of applications and are an increasingly popular learning and strategy tool (e.g. Novak and Cañas 2008 ; Stevenson, Hartmeyer and Bentsen 2017 ). It is on the rise as an instructional method (e.g. Nair and Narayanasamy 2017 ), to aid in curriculum design (e.g. Buhmann and Kingsbury 2015 ) and as an assessment tool (e.g. Marriott and Torres 2016 ). In recent years, concept maps have been used more widely as a research instrument. This includes the application of concept maps to study knowledge, explore mental models and misconceptions, or to describe people’s opinions. Figure  1 provides an example of a concept map. The focus question or prompt for the example in Fig.  1 could have been “What is a concept map?” or the topic provided could have been ‘Concept maps’.

Example of a hierarchical concept map by Ed Dole (adapted from Dori 2004 )

The words enclosed in circles are concepts, also referred to as nodes. These concepts are connected with arrows, or links, that are indicated with linking words, explaining the relation between the concepts. A proposition is a concept-link-concept combination, for instance ‘concept maps–include—hierarchies’. In this example, there are four hierarchies or strings of concepts stemming from the root concept ‘concept maps’. Links between concepts from the same hierarchy are called links. Links between concepts from different hierarchies are cross-links.

A concept map assignment includes: concepts or nodes, links or linking lines, linking phrases, and the concept map structure, and all these aspects can be either respondent driven or provided by the instructor (Ruiz-Primo 2000 ). For instance respondents think of concepts themselves, or are provided a list of concepts they can use for their concept map. In most studies that apply concept maps, at least one of these four aspects of the task is instructor-directed; most commonly, the concepts to be used are provided (Ruiz-Primo et al. 2001 ). In open-ended concept maps respondents choose their own terms for nodes, links or linking lines, linking phrases and structure, therefore they resemble the respondents’ knowledge structure (Cañas, Novak and Reiska 2013 ; Ruiz-Primo et al. 2001 ). Open-ended concept maps are graphical tools in which respondents are invited to represent their personal construction of knowledge, without instructor-directed aspects. In an open-ended concept map assignment, only a topic or prompt is provided to the respondents. For instance Ifenthaler, Masduki and Seel ( 2011 ) asked respondents to create a concept map to depict their understanding of research skills, Beyerbach ( 1988 ) asked students to draw a concept map for teacher planning and Çakmak ( 2010 ) asked respondents to generate a concept map concerning teacher roles in teaching process.

Open-ended concept maps are commonly applied to explore student knowledge, to evaluate what or how students learn or to explore misconceptions in student knowledge (Greene et al. 2013 ; Stevenson et al. 2017 ). The application of open-ended concept maps to study knowledge and learning faces new challenges concerning application and analysis, as this application transcends the traditional, strictly defined, quantitative use of concept maps in other domains, such as engineering, mathematics and psychology (Wheeldon and Faubert 2009 ). When exploring knowledge and learning, the strictly defined quantitative use of concept maps is believed not to do justice to the personal and idiosyncratic nature of people’s understanding (Novak 1990 ). Open-ended concept maps are therefore used to study people’s knowledge and understanding of complex phenomena, such as leadership or inclusive education. They are also used when respondents’ knowledge is expected to be fragmented, or when the misconceptions and/or limited nature of people’s understanding are part of the study (Greene et al. 2013 ; Kinchin, Hay and Adams 2000 ).

The variation in outcomes using open-ended concept maps as a research instrument reduces the comparability and leads to difficulty in data analysis (Watson et al. 2016a ; Yin et al.  2005 ). Previous studies describe limitations concerning methods of analysis. Several studies argue that quantitative analysis neglects the quality or meaning and learning (Bressington, Wells and Graham 2011 ; Buhmann and Kingsbury 2015 ; Kinchin et al. 2000 ). Others argue that it is an insufficient evaluation of values or perceptions as expressed by respondents (Jirásek et al. 2016 ). Some studies address contradicting outcomes when methods of analysis are compared, and they question the validity and reliability of concept map analysis and concept maps as a research instrument (Ifenthaler et al. 2011 ; Kinchin 2016 ; Watson et al. 2016a ; West et al. 2002 ). Cetin, Guler and Sarica ( 2016 ) claim that it is unclear how the reliability and validity of open-ended concept map analysis can be determined. Additionally, Ifenthaler et al. ( 2011 ) argue that some of the methods of analysis applied in previous studies have questionable reliability and validity. Tan, Erdimez and Zimmerman ( 2017 ) complement these statements by addressing the lack of clarity they perceived in the existing methods of analysis when choosing a method of analysis for their study.

This literature review explores the analysis of open-ended concept maps in previous studies. Firstly, we contemplate what aspects of the process of analysis to consider for this review, based on the quality appraisal of the process of analysis in qualitative research. Creswell ( 2012 ) emphasizes the interrelation of the steps concerning data gathering, interpretation and analysis in qualitative research. Accordingly, Huberman and Miles ( 2002 ) proposed three central validities for assessing the quality of qualitative research: descriptive, interpretative and theoretical. These are respectively concerned with the data collected or the characteristics of the data that are considered, how data are interpreted or analyzed, and the conclusions that are drawn. These three aspects should be aligned or coherent to increase the quality of research, and are therefore explored in previous open-ended concept map studies. The method of analysis applied, concept map characteristics measured, and conclusions drawn, and the associations between these aspects are explored (Chenail, Duffy, George and Wulff 2011 ; Coombs 2017 ). The research question is: Which methods of analysis are applied to open-ended concept maps when studying knowledge and learning, and how are these associated with concept map characteristics considered and conclusions drawn?

To answer the research question, we extract information concerning method of analysis applied, concept map characteristics measured, and conclusions drawn from previous open-ended concept map studies. Following guidelines for critical interpretative synthesis reviews, this review combines an aggregative and interpretative approach to critically understand the analysis in previous studies (Gough and Thomas 2012 ). The aggregation entails the representation of clusters for each aspect based on cross-case analysis, as presented in the results. Subsequently, patterns among these aspects are explored and interpreted, leading to considerations for future studies concerning these three aspects and their methodological coherence.

2.1 Selecting articles (inclusion)

This review applies a comprehensive search strategy to include all relevant studies (Verhage and Boels 2017 ). Scientific articles are selected from three databases: the Education Resources Information Center (ERIC); PsycINFO; and the Web of Science (WOS). The keywords for the search are ‘concept map’, and ‘analysis’ or ‘assessment’ or ‘scoring’. Studies are included from 1984 onward, when Novak and Gowin established the term ‘concept map.’ Due to the broad social science disciplines included in WOS, a further selection is made based on the predetermined WOS Category ‘Education educational research’, to exclude for instance geographical studies that map cities, and are not concerned with knowledge or learning but spatial planning. The combined search yields 451 studies in ERIC, 198 studies in PsycINFO and 498 studies in WOS.

Three reviews of concept maps studies are used in a selective search strategy: the open-ended concept map studies described in these reviews are included in this study (Anohina and Grundspenkis 2009 ; Ruiz-Primo and Shavelson 1996 ; Strautmane 2012 ). Based on the snowballing technique with these reviews, 85 additional studies are included, and 1316 in total, as depicted in Fig.  2 . The first review by Anohina and Grundspenkis ( 2009 ) presented manual methods of analysis, and addressed the feasibility of automating these methods. The reviews by Ruiz-Primo and Shavelson ( 1996 ) and Strautmane ( 2012 ) related methods of analysis to the openness of the concept mapping assignments. These reviews did not explore the associations between the methods of analysis and the conclusions drawn in these studies. Our review is one of the first to address the associations between the methods of analysis, the concept map characteristics considered and the conclusions drawn, instead of focusing on these aspects separately. This coherence is relevant to explore as it enhances the rigor and quality of qualitative studies, by ensuring an appropriate alignment of these aspects within studies (Davis 2012 ; Poucher et al. 2020 ).

Search and selection strategy

2.2 Screening articles (exclusion)

The selected articles are screened. 254 duplicates are excluded. Next titles and abstracts are screened. In order to increase the quality of this process, the inclusion and exclusion criteria are discussed with co-researchers until consensus is reached. 703 articles did not apply concept maps, or concept maps were used as learning tool, instructional tool, for curriculum design or to analyze answers, texts or interviews. These are excluded. For the remaining 359 studies that apply concept maps as research instrument, step 2 of the screening is based on the methods section. Studies are included based on the following inclusion criteria:

Concept maps were used as a research instrument;

The study was an empirical study;

Respondents made their own concept map; and

An open-ended concept map assignment was applied.

In seven studies, other visual drawings than concept maps were used. In 31 studies, concept map analysis was described based on theory instead of empirical data. In 71 studies, concepts map were constructed by the researcher based on interviews, together with the respondent during an interview or at group level based on card sorting techniques. In 154 studies, at least one of the aspects of the concept mapping task was instructor-directed. Studies are included if one or more focus questions or one central concept was provided.

The critical appraisal of the methods section, leads to two additional exclusion criteria (Verhage and Boels 2017 ). Seventy studies applied another research instrument alongside concept maps. For these studies, the results sections are read to discover whether concept maps were evaluated separately. In 30 studies, concept map analysis was combined with interviews or reflective notes. 36 studies compared concept map scores with results from other research instruments, such as knowledge tests or interviews. These studies were excluded because the method of analysis or conclusions for the concept maps was not described separately. This is problematic for our research purposes, as this study is concerned with concept map analysis and conclusions based on concept maps analysis, and not analysis and conclusions based on other instruments. Four studies that applied two instruments—but reported on the analysis of concept maps separately—are included.

For step 3 of the selection process, the full texts of the remaining 30 studies are read. Five studies are excluded; in two studies, different concept map characteristics are summed up and not described separately. One study calculated correlations between different concept map characteristics, and two studies drew conclusions purely on group level, resulting in 25 studies being included in this review, as depicted in Fig.  2 .

2.3 Data selection from articles

Information on the following topics is extracted from the articles: the method of analysis, the concept map characteristics, the conclusions, the rationale behind the choices made, and general or descriptive information. A data selection scheme is developed which depicts the extracted information (Table 1 ). To increase the reliability of the data selection, this scheme was continuously discussed and adjusted by the authors over the entire selection process. Reliability was further ensured by using signal words, based on common terms used in the studies. For three of the studies included, the data selection was performed independently by two researchers. Both researchers selected statements from the articles concerning the items described in Table 1 . One researcher included 79 statements and the other 94 statements. The statements selected by the researchers overlapped completely. The 15 statements only selected by one researcher were discussed and added to the data. A total of 109 citations were extracted from these three studies.

2.4 Data analysis

Data analysis is performed by using the selected articles for within- and cross-case analysis (Miles and Huberman 1994 ). In this review, the cases are the articles included. The first step of analysis is to order the extracted information in a meta-matrix (see " Appendix A ") that presents all relevant condensed data for each case or article separately (Miles and Huberman 1994 ). If no explicit statements are found, information is added by using the within-case analytic strategy of ‘overreading’ (Ayres, Kavanaugh and Knafl 2003 ). For instance, for a study that counted specific concept map characteristics but did not describe the method of analysis any further, the method of analysis was described as quantitative analysis. To prepare data for cross-case analysis, different labels for the same aspect are unified. For instance, ‘counting nodes’ is relabeled as ‘number of nodes.’

The second step entails coding the selected statements concerning the research object, research design, methods of analysis, concept map characteristics, and conclusions drawn in the articles, using a cross-case analysis approach. Preliminary coding of statements concerning methods of analysis is based on the way studies refer to their method of analysis. However, the same term was sometimes used to refer to more than one analysis method, while in other cases, multiple terms were used to refer to a single method. Thus, the designation of clusters based on how the studies referred to their methods of analysis proved inconclusive and ambiguous.

Different distinctions between methods of analysis are found in the literature. For example, in the review by Anohina and Grundspenkis ( 2009 ) the use of an expert’s map is one choice, as well as the choice for quantitative or qualitative analysis and structural or relational analysis, to make a distinction between methods of analysis. In the review by Strautmane ( 2012 ), the criteria for similarity analysis, e.g. “proposition similarity to expert’s CM”, or “convergence with expert’s CM”, are described as separate criteria. Also in the review by Ruiz-Primo and Shavelson ( 1996 ), comparison with a criterion map, is described as a separate method of analysis. In this review, the distinction between quantitative, qualitative, similarity and holistic analysis is chosen, as these methods of analysis consider the concept map characteristics distinctively and they are based on different principles and theoretical assumptions. Holistic analysis is a separate method of analysis, as it is based on a rubric, and similarity is a separate analysis, as it is based on a reference map. Moreover, these four methods of analysis lead to different types of conclusions, and are therefore considered as distinctive ways to analyze and interpret data from concept maps. In conceptual terms, these four methods of analysis are mutually exclusive, as they estimate the concept map characteristics differently. However, when applied to analyze data, they can be combined: similarity analysis compares concept maps to a reference map, either qualitatively or quantitatively.

The statements concerning concept map characteristics are unified; for instance, ‘breadth and depth’ or ‘hierarchical structure of the map’ were both coded as structural complexity. All concept map characteristics related to the semantic content of the map, referred to as ‘terms used’, ‘content comprehensiveness’, ‘correctness’ or ‘sophistication’, are clustered as semantic sophistication. The conclusions are clustered in the same way as the methods of analysis. Conclusions about numbers of concept map characteristics are labelled as quantitative, conclusions about descriptions are labelled as qualitative, conclusions about overlap with a reference map are labeled as similarity and conclusions about the quality of the map as a whole are labelled as holistic.

For the same three studies that two researchers selected statements from independently, the statements were coded by two researchers independently. A total of 109 statements were coded. Krippendorf’s alpha of the inter-rater agreement was 0.91. The discrepancies in coding were all related to concept map characteristics. For instance, counting cross-links was coded as interlinkage by one researcher and as structural complexity by the other researcher, while the validity of links was labeled as semantic sophistication by one researcher and category representation by the other. The first author coded the data from the remaining 22 articles included in the review and consulted the co-authors when in doubt.

The third step of the analysis was exploring the associations between the methods of analysis, concept map characteristics and conclusions drawn. Across all articles, the associations between the choices made in these three areas were explored. For instance, for all studies that applied quantitative analysis, the concept map characteristics considered were explored and listed. This showed that quantitative analysis was concerned with specific concept map characteristics, e.g. size, structural complexity, category representation, interlinkage or complexity index. Subsequently, the conclusions drawn were explored for each combination of methods of analysis and concept map characteristics considered. Based on the associations found across articles between the methods of analysis applied, the concept map characteristics considered and the conclusions drawn, considerations for methodological coherence between these aspects were formulated.

Twenty-five empirical studies from 1988 through 2018 used open-ended concept maps. Twenty-one of these studies consisted of multiple measurements, most commonly a pre-test/post-test design. Four of these studies compared two experimental groups, and two compared an experimental and control group. Two of the four studies that consisted of one measurement compared two experimental groups. In two studies, respondents received their previous concept map to adjust in the post-test, and in one study respondents could choose to adjust their previous map or to start a new one. Concept maps were either made on paper with pen, on sticky notes or on a computer, most commonly with the CMapTool, developed by the Florida Institute for Human and Machine Cognition. " Appendix A " provides the meta-matrix of these studies, including all selected information. For each aspect (method of analysis, concept map characteristics, and conclusions) the categorization or clustering based on the cross-case data analysis is presented in separate paragraphs. How concept map characteristics are associated with methods of analysis is described in the paragraph concerning the concept map characteristic. How conclusions drawn are related to concept map characteristics and methods of analysis is described at the end of the paragraph concerning conclusions drawn.

3.1 Methods of analysis

The different methods of analysis as described in the studies are extracted and presented in the table below. The explanation of these methods of analysis is provided after Table 2 .

Based on these studies it appears that the same term was sometimes used to refer to more than one analysis method, while in other cases, multiple terms were used to refer to a single method. These varieties increase the ambiguity experienced with concept map analysis, as described by Watson et al. ( 2016b ). Based on the ways in which concept map characteristics are estimated, we propose the following distinction: quantitative, similarity, holistic and qualitative analysis. Quantitative analysis, or counting concept map characteristics, was performed absolutely or relatively—for example, the number of links was counted separately or calculated in relation to the number of nodes. Category representation was also determined absolute, as the number of nodes belonging to a category, or relative, dividing the number of nodes belonging to a category by the total number of nodes in a map. These different calculations can result in different conclusions. According to Besterfield-Sacre and colleagues ( 2004 , p. 113), quantitative analysis “fails to capture the quality of that content. Further, these scoring methods can be time consuming, lack standards, and may introduce inappropriate bias.”

Similarity analysis described or calculated the percentage of overlap and/or discrepancy compared to a reference map. To calculate percentage of overlap, the terms used by respondents need to be aligned with the reference map. Similarity analysis provided insights into the (degree of) overlap and discrepancies with a reference map and was performed manually or in an automated manner (Ifenthaler et al. 2011 ).

Holistic analysis included scoring the structure or content for the concept map as a whole. Besterfield-Sacre and colleagues ( 2004 ) developed the scoring rubric that was commonly used for holistic analysis. They developed this rubric to score the overall comprehensiveness, organization and correctness of the map, based on the topics experts discussed while analyzing concept maps. Holistic analysis was determined on an inter-rater basis and is a cognitive complex task for which subject matter knowledge is necessary; this scoring is subjective (Borrego et al. 2009 ; Yaman and Ayas 2015 ).

Qualitative analysis of semantic content was performed in most studies, either inductively or deductively to determine categories. Qualitative analysis was the only way to explore concept maps content inductively.

Most studies applied more than one method of analysis. Quantitative analysis was applied in 19 studies, qualitative analysis also in 19 studies, holistic analysis in six studies and similarity analysis in five studies. Why methods of analysis were chosen is described in several studies. Ritchhart and colleagues ( 2009 , p. 152) stressed that qualitative analysis “allowed us to best represent all of the data from the maps”. Beyerbach ( 1988 , p.339) applied qualitative analysis, as it revealed “the nature of growth of student teachers’ thinking [..] and conceptual development”. Quantitative analysis was chosen as it “demonstrates the student learning gains” (Borrego et al. 2009 , p.14). Similarity analysis was performed as “Comparisons of the students' maps to an expert's map will provide information regarding how much is learned from the course and whether the concepts that are learned and included in the maps are done so "correctly" and as intended according to the expert-the faculty instructor” (Freeman and Urbaczewski 2002 , p. 42). Besterfield-Sacre et al. ( 2004 , p. 109) choose holistic scoring to explore students’ conceptual understanding, as an increase in understanding results “in higher quality maps as reflected by the holistic score.”

3.2 Concept map characteristics

This section describes what concept map characteristics were measured, how and why. Table 3 provides an overview of the results. The concept map characteristics described in this review concern characteristics as portrayed in the included studies. These include characteristics concerning the structure of concept maps, such as size, structural complexity and type of structure, and characteristics concerning the content of concept maps, for instance the terms used or categories represented in concept maps. The different concept map characteristics as portrayed in the included studies are presented below.

The number of nodes was referred to as the size or extent, and considered as “a simple indicator for the size of the underlying cognitive structure” (Ifenthaler et al. 2011 , p. 55). Size was established by counting the number of unique or correct nodes or propositions. Invalid nodes were included to study mental models or when misconceptions were important.

3.2.2 Structural complexity

Structural complexity is concerned with how complex the structure of a concept map is. The concept map nodes and links were used to study structural complexity quantitatively, holistically or in similarity. The scoring system for structural complexity from Novak and Gowin ( 1984 ), based on the number of hierarchies, cross-links and examples, was applied in seven studies, and these measures were adjusted in four of these studies. Specific aspects of structural complexity, were breadth or number of hierarchies and depth or hierarchy level (Beyerbach 1988 ; Read 2008 ). Other references to structural complexity, all calculated based on the number of links, are complexity, connectedness or dynamism and these measures are more commonly used for non-hierarchical concept maps (Ifenthaler et al. 2011 ; Tripto et al. 2018 ; Weiss et al. 2017 ). Freeman and Urbaczewski ( 2002 , p. 45) computed structural complexity as the number of relationships depicted in the map beyond the minimal amount necessary to connect all of the concepts linearly. Ifenthaler and colleagues ( 2011 ) included computations from graph theory, such as unlinked nodes that are not connected to the other nodes, the cyclic nature of a map, i.e. if all nodes can be reached easily, or the longest and/or shortest paths from the central node. Structural complexity was also scored based on a rubric, taking into account the overall organization of the map. For instance a score of 1 if the concept map is connected only linearly, a score of 2 when there are some connections between hierarchies, or a score of 3 for a sophisticated structure (Besterfield-Sacre et al. 2004 ). Another way to score structural complexity is by comparing structural characteristics with a reference map (Ifenthaler et al. 2011 ).

The analysis of structural complexity is more sensitive in measuring change than other analyses (West et al. 2000 ). However, the limited hierarchical interpretation of structural complexity based on quantitative analysis can lead to different scores than holistic scoring of structural complexity (Watson et al. 2016a ). According to West and colleagues ( 2000 , p. 821), scoring structural characteristics “[becomes] more difficult as maps grow more complex,” and Blackwell and Williams ( 2007 , p. 7) mentioned that scoring structural characteristics “can conceal the essentially subjective basis on which it rests.”

3.2.3 Type of structure

Studies concerned with the type of structure or shape of the map categorized concept maps qualitatively based on global morphologies. Global morphologies are common typical structures found in concept maps, such as chain, spoke or net structures, as depicted in Fig.  3 . This analysis provides a measure for the aptitude for learning and “avoids many pitfalls of quantitative analysis” (Hay et al. 2008 , p. 224). Yaman and Ayas ( 2015 , p. 853) categorized concept maps based on their type of structure, and stated that it was “very easy and informative.”

Global morphologies in concept maps (from Kinchin, Hay and Adams 2000 )

3.2.4 Semantic sophistication

Semantic sophistication is concerned with the terms as used by the respondents, for concepts as well as for links. Semantic sophistication was explored by describing or clustering the terms used by the respondents qualitatively. Analysis of the semantic sophistication or content revealed the information in concept maps and what respondents think (Kostromina et al. 2017 ; Ward and Haigh 2017 ): “These qualitative analyses go beyond traditional assessment techniques in providing the instructor with a much clearer view of what his/her students know, think, and understand” (Freeman and Urbaczewski 2002 , p. 51). Semantic sophistication was also scored based on a rubric, taking into account the comprehensiveness or correctness of content, and whether maps conformed to fact, logic or known truth (Besterfield-Sacre et al. 2004 ). Gregoriades and colleagues ( 2009 ) described how holistic scoring allowed them to assess overall understanding. The semantic sophistication was also measured in comparison to a reference map. Beyerbach ( 1988 , p. 341) calculated “convergence towards a group consensus, and convergence toward an expert's map to indicate conceptual growth.” Freeman and Urbaczewski ( 2002 , p. 42) compared students’ maps to an expert’s map to assess how much was learned and whether the learned concepts were integrated correctly.

3.2.5 Category representation

Category representation is concerned with categories of nodes and/or links in concept maps. Different types of categories were established, either valid and invalid nodes or propositions, where invalid nodes are outside of the scope of the prompt, and invalid propositions are incorrectly linked. Another category was old and new nodes in repeated measures, where old nodes were already present in the first map, and new nodes were added in the second map. Also content-related categories were distinguished, for instance concepts at different levels. One study distinguished different system levels, in order to reveal students’ systems thinking abilities—or, more specifically, students’ “ability to identify system components and processes at both micro and macro levels” (Tripto et al. 2018 , p. 649). Category representation can only be calculated quantitatively after categories are determined in maps qualitatively. Category representation was calculated by the number of nodes per category and was also referred to as knowledge richness, frequencies of themes, presence of systems, representational level or category distribution (Çakmak 2010 ; Kostromina et al. 2017 ; Ritchhart et al. 2009 ; Tripto et al. 2018 ; Yaman and Ayas 2015 ). Ritchhart and colleagues ( 2009 , p. 154) calculated the percent of responses in each category. Çakmak ( 2010 ) studied perceptions about roles based on the number of concepts assigned to each role.

3.2.6 Interlinkage

Interlinkage concerns the links between categories, and can only be calculated after categories are established. Interlinkage was also referred to as ‘complexity’ or ‘degree of interconnectedness.’ Interlinkage was interpreted as “students’ ability to identify relations between system components” (Tripto et al. 2018 , p. 649). Specifically, the interlinkage between old and new nodes was used to study learning, or how new knowledge is connected to existing knowledge (Hay et al. 2008 ). Güccük and Köksal ( 2016 ) explored meaningful learning based on the number of interlinks and interpreted more interlinks as more meaningful learning. Ward and Haigh ( 2017 , p. 1248) concluded that the analysis of interlinkage between old and new nodes allowed for holistic examination of the quality of learning.

3.2.7 Complexity index

The complexity index is calculated based on the number of concepts, number of categories, and number of links between categories. It was calculated in two studies to “characterize the overall coverage of and connectedness between the categories” (Watson et al. 2016b , p. 549). The complexity index is a particularization of interlinkage, calculated by dividing the number of interlinks by the number of categories, then multiplying this number with the number of nodes (Segalàs et al. 2012 , p. 296).

A variety of concept map characteristics was considered, leading to different insights. Size was measured in 18 studies. Structural complexity was also taken into account in 18 studies. Structural complexity considered nodes and links and seems relatively easy and objective to determine; however, it is more interpretative than it seems, especially as concept maps grow more complex. Type of structure was measured in three studies, and revealed the overall structure of the concept map, disregarding the content and allocating one score for the overall structure of the map. Although it is a time-consuming step to describe and interpret terms used by respondents, this is the only way to gain insights into the semantic content of the maps. The semantic sophistication was taken into account in 13 studies. Terms used were sorted into themes or categories, which was done in eleven studies, either inductively or deductively, based on a theoretical framework or scoring rubric, or in comparison with a reference map. Evaluating the terms used and categorizing or unifying them was a necessary preliminary step for calculating other concept map characteristics, namely: category representation, interlinkage and complexity index. These characteristics were only considered when meaningful categories were present and interconnection of these categories was convenient, for instance, in the case of systems thinking. Interlinkage was determined in five studies and the complexity index in two studies.

Explanation of the rationale for concept map characteristics and measures varied from just mentioning which characteristics are measured and how, to studies that explain their operationalization based on theoretical descriptions of the research object that is explicitly deduced into specific concept map characteristics and measures. Some studies explicitly explained the choice for concept map characteristics based on the conclusions to be drawn. For instance Besterfield-Sacre et al. ( 2004 , p.106) explain counting cross-links as follows: “We propose that measuring inter-relatedness is a way to assess the extent of knowledge integration.” How concept map characteristics were related to methods of analysis, is described in Table 3 .

3.3 Conclusions drawn in the studies

The different conclusions drawn in the included studies about knowledge or learning are presented below. Conclusions about knowledge, for instance knowledge extent, were based on the number of nodes (Gregoriades et al. 2009 ). In repeated measures, an increase in number of nodes was interpreted as “more detail” (Beyerbach 1988 , p. 345) or “greater domain knowledge” (Freeman and Urbaczewski 2002 , p. 45). Counting the nodes was performed to “quantify knowledge understanding” (Besterfield-Sacre et al. 2004 , p. 105). Conclusions about an “increase in richness” (Van den Boogaart et al. 2018 , p. 297) or “balanced understanding” (Watson et al. 2016b , p. 556) were based on counting the number of nodes per category. Conclusions about better coverage and interconnectedness or systemic thinking were based on the complexity index (Segalàs et al. 2012 ). Conclusions about what respondents knew, or in repeated measures about how their knowledge changed over time were based on describing the content of concept maps (Freeman and Urbaczewski 2002 , p. 42). It “revealed that teachers assign a significant role both to its own activity and activity of the University administration, as well as cooperation with students” (Kostromina et al. 2017 , p. 320).

Conclusions about the complexity of knowledge, or the complexity of the knowledge structure, were based on the number of links. For instance, a conclusion about “more complex constructions of their knowledge” was based on the number of links, or structural complexity of concept maps (Read 2008 , p. 127). In repeated measures, conclusions about “conceptual growth” were drawn based on structural complexity measures (Beyerbach 1988 , p. 342). Conclusions about knowledge integration and learning gains (Borrego et al. 2009 ) were based on scoring the structural quality of concept maps based on a rubric and, in repeated measures, about additional conceptual understanding (Besterfield-Sacre et al. 2004 ; Watson et al. 2016b ). Conclusions about the use of semantically correct concepts (Ifenthaler et al. 2011 ), or correct integration of concepts (Freeman and Urbaczewski 2002 ), were based on a comparison with a reference map. Other conclusions drawn based on comparison with a reference map were that students have significant misconceptions (Gregoriades et al. 2009 ), or that respondents gained a better understanding (Freeman and Urbaczewski 2002 ; Ifenthaler et al. 2011 ). Conclusions about meaningful learning were based on counting the number of links between old and new concepts (Hay 2007 ). Conclusions about development were also based on the type of structure of concept maps in repeated measures. Conclusions drawn based on the type of structure were in one study, that pre- and post-maps were both mainly non-hierarchical (Yaman and Ayas 2015 ), and in one study, that 16 of 18 respondents’ pre- and post-maps showed “remarkable structural homology, even where the content and its internal organisation were different” (Hay et al. 2008 , p. 233).

Most studies applied more than one method of analysis and combined concept map characteristics when conclusions were drawn. Two of the three studies applying one method of analysis, qualitatively described the terms used in maps. The other study that applied one method of analysis, explored the semantic sophistication and structural complexity holistically. All other studies analyzed at least one concept map characteristic with two methods of analysis (for instance combining quantitative and similarity analysis of structural complexity), but most commonly multiple concept map characteristics and multiple methods of analysis were applied. However, a conclusion concerning counting different concept map characteristics was that it has shown opposing results within several studies: “While cross link scores were lower in some cases, hierarchy scores increased dramatically demonstrating that students were seeing each proposition in greater depth” (Blackwell and Williams 2007 , p. 6). Or in the study of Freeman and Urbaczewski ( 2002 ), where structural complexity scores decreased while all other scores increased. In all studies, an increase in a measure or concept map characteristic was interpreted as conceptual development or growth, and in all but one repeated measures studies, development was found. This particular study described the main themes based on qualitative analysis of the terms used, without interpreting this as development. Two studies mentioned that the number of links or cross-links did not increase, and two studies found homogenous types of structures, but still concluded that understanding increased, mainly based on other measures.

Although most studies draw conclusions about conceptual understanding or in repeated measures about conceptual growth, conclusions drawn are related to the methods of analysis applied and concept map characteristics considered. Conclusions about an increase or growth, are mainly based on counting structural concept map characteristics, or applying quantitative analysis. Conclusions about meaningful learning and more balanced understanding, were also based on quantitative analysis. Conclusions about knowledge, learning or conceptual growth, or integration of knowledge were based on a comparison with a reference map. Conclusions concerning knowledge integration, learning and coverage were based on holistic analysis. Conclusions about the content of maps, and what respondent know or what themes they mention, were based on qualitative analysis of terms used.

4 Conclusion

The central research question was: Which methods of analysis are applied to open-ended concept maps when studying knowledge and learning, and how are these associated with concept map characteristics considered and conclusions drawn? The conclusions are presented based on the three main aspects of the research question, namely methods of analysis, concept map characteristics and conclusions drawn, as well as their mutual associations.

4.1 Methods of analysis

This review explored the methods of analysis applied in open-ended concept map studies and provided a first step towards exploring which methods of analysis are applied and how. Four categories of methods of analysis were identified, namely: (1) quantitative analysis based on counting concept map characteristics; (2) similarity analysis based on a comparison with a referent map; (3) holistic analysis that entails the scoring of maps as a whole based on a rubric; and (4) qualitative analysis that involves describing characteristics, for instance the terms used.

The 25 studies applied different methods of analysis. Due to the idiosyncratic nature of the data stemming from open-ended concept maps they can be analyzed in different ways (Novak 1990 ). Qualitative and quantitative analysis are most commonly applied to open concept maps, but to make concept maps more comparable, it is common to use both methods, in which case quantitative analysis is preceded by qualitative analysis. Quantitative analysis is performed to count differences between maps. Similarity analysis explores the overlap with a reference map based on the nodes or structural characteristics. Holistic analysis scores the structure and content of concept maps. Qualitative analysis is used to explore or describe concept map characteristics and to explore the uniqueness of each map.

Each method of analysis deals with the idiosyncratic data differently. Qualitative analysis of semantic sophistication is the only way to explore the idiosyncratic nature of open-ended concept maps and the terms for concepts as the respondents use them. Quantitative analysis reduces the unique terms respondents use to numbers. Similarity and holistic analyses value the terms used based on an existing framework and provide a score for overlap or correctness respectively. When an open-ended concept map is used to gather the unique terms respondents use and there is no correct map available, qualitative analysis is required to explore or describe this information or to make quantitative analysis more meaningful.

4.2 Concept map characteristics

Concept map characteristics are not always explicitly described, and many different descriptions are used for similar concept map characteristics. This study distinguished between seven concept map characteristics as described in the included articles. Concept map characteristics that were counted or evaluated quantitatively are size, structural complexity, category representation, interlinkage and complexity index. These are all related to structure, except for category representation, as this referred to the number of concepts per category. The type of structure, semantic sophistication, categories and interlinkage can be described or evaluated qualitatively. These are all related to the content of the map, except for type of structure. The structural complexity and semantic sophistication can also be evaluated in relation to a reference map based on a rubric. Similarity and holistic methods of analysis combine structural and content-related features of concept maps.

4.3 Conclusions drawn in the studies

Our review shows that although the methods of analysis vary, the conclusions drawn are quite similar. Despite whether concept map characteristics were counted, compared, scored or described, conclusions were drawn about understanding or conceptual growth in repeated measures. All studies with repeated measures applying quantitative analysis found an increase of a measure that was interpreted as conceptual growth. Similarity analysis in repeated measures revealed an increased overlap in specific measures, which was considered as development of understanding. Holistic analysis revealed that better understanding or knowledge integration was found in repeated measures. Three studies used qualitative analysis to identify conceptual growth, for instance, the concept of leadership, where students considered leadership more as a process in the post-test. Twenty of the 21 studies with repeated measures found some type of development or learning gains, most commonly referred to as conceptual growth.

4.4 Associations across articles

Associations were explored between the coding of the methods of analysis, the concept map characteristics, and the conclusions drawn, in order to provide guidelines for methodological coherence between these aspects. Figure  4 provides an overview of the types of conclusions that can be drawn from open-ended concept maps, in accordance with the identified methods of analysis and concept map characteristics.

Associations between methods of analysis, concept map characteristics and types of conclusions

Figure  4 can serve as a guide for future open-ended concept map studies which use the specific types of conclusions to be drawn as a means of deciding what method of analysis to apply and what concept map characteristics to consider. For instance, in cases of quantitative analysis, Fig.  4 suggests that no conclusions can be drawn about correctness or quality, only about the extent of domain knowledge, and an increase or decrease in repeated measures. In similarity analysis, correct and incorrect nodes and links are determined, based on a correct model. Therefore, conclusions can be drawn concerning correctness. When applying a rubric for holistic scoring, one overall score is often given for the entire map, in which the overall quality is scored (Besterfield-Sacre et al. 2004 ). Quality of content includes correctness, but only for the map as a whole. The concept map characteristics of size, category representation and semantic sophistication consider the nodes and lead to conclusions about knowledge. The concept map characteristics of structural complexity, interlinkage, complexity index and type of structure consider both the nodes and the links and lead to conclusions about knowledge structure or integration. By explicitly using the conclusion to be elicited as a basis for choosing methods of analysis and concept map characteristics, the transparency of research increases, which enables better quality assessment (Coombs 2017 ; Verhage and Boels 2017 ).

5 Discussion

When relating these conclusions to broader theory, the first point of discussion is that 20 out of 21 repeated measures studies identified learning or conceptual growth. This raises the question whether all development is interpreted as development, and whether an increase in nodes and links represents better understanding or not. Rikers, Schmidt and Boshuizen ( 2000 ), who studied encapsulated knowledge and expertise in diagnosing clinical cases, found that the proportion of encapsulating concepts increases as an indicator of expertise development. This entails a decrease in the number of nodes and links as expertise develops, as experts are able to differentiate between concepts and relationships that are more and less relevant according to a specific contexts. Accordingly, Mintzes and Quinn ( 2007 ) explore different phases in expertise development based on meaningful learning theory. Their distinction between phases of development is based on the number of expert concepts, which in turn are relevant superordinate concepts that are absent from novices’ concept maps. Accordingly, Schwendimann ( 2019 ), who studied the process of development of concept maps, also found differences between novices and experts mainly in the professional terminology experts use for their concepts and linking words. Therefore, the conclusion that an increase is always better is contradicted by many studies of expertise development in the field of cognitive science (Chi, Glaser and Farr 1988 ).

Our review did not aim to discuss the value of open-ended concept maps as an instrument to study knowledge or knowledge development. Nor did it aim to explore the validity of different methods of analysis, or determine which method of analysis is most valid, as these methods of analysis can be related to different research purposes or research objects (Kim and Clariana 2015 ). Quantitative analysis is based on an evaluative approach which assesses knowledge or growth based on specific measures or characteristics, such as size or complexity. Similarity and holistic methods analyze concept maps from expected structures or content and have an evaluative or prescriptive purpose. Similarity analysis and holistic analysis take a more normative approach to the analysis of open-ended concept maps, by comparing them to a reference map or scoring the map based on a rubric, respectively. On the other hand, qualitative analysis has a more explorative purpose. Merriam and Grenier ( 2019 ) explain similar purposes of qualitative research methods and point out that more open or qualitative analysis is suited to more explorative purposes, while more restricted approaches are more appropriate for evaluative purposes.

This review has several limitations. Only studies applying open-ended concept maps to study knowledge and learning were included. The results of this study could be different when reviewing studies that apply more closed concept maps, or studies that combine the application of concept maps with other research instruments. Also, the research objects are not included in Fig.  4 , as references to research objects were ambiguous in previous studies and it was unclear whether studies referred to the same objects differently, or studied different objects. As a result, this review focused on the process of analysis, disregarding what aspects of knowledge or learning were studied. Moreover, Fig.  4 provides no guidelines for alignment with other aspects of coherence in qualitative studies, for instance the philosophical positioning, the fundamental beliefs or theoretical perspective taken (Caelli et al.  2003 ; Davis 2012 ).

The findings in this review could be substantiated by further research exploring implicit choices or implicit methodological coherence that could not be extracted from the articles. This could take the form of interviews with the authors of the studies about their methodological assumptions, approaches and chosen methods of analysis. They could then be asked why and how they made choices related to their research object, the concept map characteristics they considered and the conclusions they drew.

While previous reviews by Ruiz-Primo and Shavelson ( 1996 ), Anohina and Grundspenkis ( 2009 ) and Strautmane ( 2012 ) explored aspects of the process of analysis separately, or related the method of analysis applied to the level of openness of the concept map task, this review examined three aspects of the analysis process in coherence. By doing so, the present study aims to inform the ongoing discussion in social sciences and beyond about the quality of analysis. Unfortunately, open-ended concept map studies often still feature ambiguous language use. This ambiguity decreases transparency about the method of analysis, the concept map characteristics, and, ultimately, the conclusions drawn and the methodological coherence of these aspects (Chenail et al. 2011 ; Seale 1999 ). Clarifying which approach is chosen to make sense of the information in open-ended concept maps provides a method of dealing with idiosyncratic information provided by the respondents and will support other researchers or policy makers to better interpret and value the conclusions drawn. By describing studies on the basis of the proposed distinction between methods of analysis applied and how they interpret or value information from concept maps, the constraints of each method can be discussed, and findings or conclusions can be understood with a degree of confidence (Chenail et al. 2011 ). This distinction between methods of analysis can enhance transparency about the conclusions to which a specific method of analysis can and cannot lead. Clarity about the choices within and across studies is stimulated by uniform referencing to these choices, which decreases the confusion caused by the variety of ways in which scholars refer to similar constructs. In future research, the guidelines provided in this study will assist scholars to make more informed choices for their analysis of idiosyncratic data gathered with open-ended concept maps.

Data availability

The data that support the findings of this study are the papers as mentioned in the results and summarized in Appendix A. They are also indicated with an * in the references section of this review. The materials used to code this data are provided in the article. The condensed data that support the findings of this study are available on request from the corresponding author Kirsten de Ries. The data are not publicly available due to the fact that not all these paper are Open Access.

Code availability

No computer codes or mathematical algorithm is used in this paper. The coding of our data was performed by the authors based on the coding scheme presented in the data section.

References indicated with * were included in the literature review

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Literature Review Example

A literature review is a summary of the existing knowledge and research on a particular subject. by identifying gaps in the literature, it provides a foundation for future research. as such, it’s a crucial first step in any research project., what is a literature review.

A literature review serves several purposes:

• identifies knowledge gaps
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Looking at existing examples of literature reviews is beneficial to get a clear understanding of what they entail. Find examples of a literature review by using an academic search engine (e.g. Google Scholar). As a starting point, search for your keyword or topic along with the term "literature review".

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Define the research question

Identify the research question or topic, making it as narrow as possible. In this example of a literature review, we review the anxiolytic (anti-anxiety) activity of Piper methysticum , or Kava .

Search for relevant literature

Searching for relevant studies is arguably the most important aspect of the literature review.

Start by identifying keywords and phrases related to the topic and use them to search academic journals and databases ( Google Scholar , BASE , PubMed , etc.). For our example, the initial search terms are " Piper methysticum anxiety" or " Piper methysticum anxiolytic", although these may change over time. For instance, kavalactones are the primary active ingredient in kava, so we may also search for "kavalactones anxiety".

Tools like the Litmaps Seed Map provide an efficient way to discover new sources by visualizing connected papers based on the number of citations and their date of publication.

In this example of a literature review focused on the anti-anxiety activities of Kava, we use the Litmaps Seed Map tool . The most recent and relevant papers can be easily identified by considering the date and number of citations.

Litmaps Discover visualizes how sources are connected and provides links to similar papers.

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Use a research-friendly note-taking software, like Obsidian , that provide #tags to keep track of key concepts.

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In this example of a literature review on Kava, the authors clearly organize the collected sources by type of study and further subdivide based on application. The discussion evaluates the evidence altogether and addresses gaps in the literature.

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Mapping reviews, scoping reviews, and evidence and gap maps (EGMs): the same but different— the “Big Picture” review family

• Fiona Campbell   ORCID: orcid.org/0000-0002-4141-8863 1 ,
• Andrea C. Tricco 2 ,
• Zachary Munn 3 ,
• Danielle Pollock 3 ,
• Ashrita Saran 4 ,
• Anthea Sutton 5 ,
• Howard White 6 &
• Hanan Khalil 7  

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Scoping reviews, mapping reviews, and evidence and gap maps are evidence synthesis methodologies that address broad research questions, aiming to describe a bigger picture rather than address a specific question about intervention effectiveness. They are being increasingly used to support a range of purposes including guiding research priorities and decision making. There is however a confusing array of terminology used to describe these different approaches. In this commentary, we aim to describe where there are differences in terminology and where this equates to differences in meaning. We demonstrate the different theoretical routes that underpin these differences. We suggest ways in which the approaches of scoping and mapping reviews may differ in order to guide consistency in reporting and method. We propose that mapping and scoping reviews and evidence and gap maps have similarities that unite them as a group but also have unique differences. Understanding these similarities and differences is important for informing the development of methods used to undertake and report these types of evidence synthesis.

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Introduction

Evidence synthesis(defined broadly as the rigorous collation, evaluation and analysis of literature, studies, and reports) is increasingly viewed as critical to inform decision making in policy and practice. Over the past three decades, as various methods of evidence synthesis have emerged and evolved, the systems and labels used to categorize different review types have proliferated. A recent catalog of evidence synthesis approaches and terms identified 48 distinct review types [ 1 ]. Moher et al. (2015) [ 2 ], describes them as a “family” of evidence synthesis products that have arisen in response to policymakers and other stakeholders needs for diverse forms of information. This growth reflects the increased value placed on evidence synthesis to inform decision making, and we now see evidence synthesis used to address a broader range of research questions beyond effectiveness, along with tailored approaches (in terms of methods and products) to evidence synthesis as appropriate for different research needs, purposes, situations, and audiences [ 3 ].

Examples of approaches that are increasingly seen in the published literature are scoping reviews, mapping reviews, and evidence and gap maps (EGMs). Scoping reviews, mapping reviews, and EGMs are relatively new approaches that rarely appeared before 2009 [ 4 , 5 ]. Scoping reviews, evidence maps, and evidence and gap maps have been grouped together as “Big Picture” approaches due to their shared purpose and approaches. These Big Picture reviews can be contrasted with systematic reviews (addressing interventions, diagnostic test accuracy, prognosis, etc.) as they have a broader scope as compared to the (normally) narrower scope of classic systematic reviews. There have been consistent yearly increases in the publication of scoping, mapping, and evidence and gap maps [ 6 ]. Despite this, there remains confusion as to their application, meaning, and whether differences exist between them. This commentary aims to clarify these approaches, identify any differences between them, and provide recommendations for reviewers.

Terminology matters

This growing and evolving family of evidence synthesis types presents some challenges [ 7 ].

Firstly, there is the challenge of choosing the correct approach, particularly when terms are used inconsistently in the literature. The selection of an appropriate review approach will ensure the correct methods are employed using the appropriate standards for both its conduct and reporting. Indexing and wider dissemination can be challenging for researchers when there is ambiguity in terms [ 8 , 9 ].

Scoping reviews and mapping reviews—how are they used in the literature

Scoping reviews, mapping reviews, and evidence maps are terms that are not used consistently in the literature, with different terms used to describe similar approaches and review objectives. The same term is also used to describe different approaches and review objectives. Within the published literature, the terms scoping reviews and mapping reviews appear to be used in three different ways. Firstly, the terms “mapping” and “scoping” reviews are used interchangeably, referring to the same type of review methodology [ 5 , 6 , 10 ]. This approach is also one that is used in the PRISMA Extension for Scoping Reviews (PRISMA-ScR) [ 11 ], providing guidance to inform reporting standards [ 12 ]. This may therefore have been influential in increasing the use of the term scoping review over the use of the term mapping review. Examination of published reviews does not reveal differences in method between these approaches (Campbell et al., 2022 publication in press).

Secondly, we see the terms used as complementary to the other. Some definitions tend to use the terms in a way which suggest that mapping is a specific approach to scoping—or vice versa. For example, “scoping reviews can usefully map the evidence in a number of ways” [ 13 ] and “scoping reviews are a way of mapping the key concepts” [ 14 ]. Lukersmith et al. (2016) [ 15 ] and Fernadez-Sotos et al. (2019) [ 16 ] suggest that the term map is a descriptive term used to describe one of the purposes of the scoping review. A mapping review may also scope the literature. It has also been suggested that when the term mapping is included in the description of the method that the review will incorporate a geographical mapping exercise or charting of the data in a tabular or any other visual format that can plot or portray the data.

Finally, we see scoping and mapping used to describe different types of evidence synthesis, and a distinction is made between mapping and scoping reviews [ 1 , 17 ]. These authors suggest that scoping reviews are “preliminary assessment of potential size and scope of available research literature which aims to identify nature and extent of research evidence (usually including ongoing research)”. It also is a term that has emerged within the systematic review field to describe the preliminary work undertaken with information specialists in planning the review, by getting a sense of the size of the literature, to identify key terms and theories and potentially clinical experts [ 18 ]. Within these definitions, mapping reviews are distinguished from a scoping review because the subsequent outcome may involve either further review work or primary research and this outcome is not known beforehand. For the purpose of this paper, we will refer to these as a scoping exercise instead of a formal scoping review methodology. Scoping exercises within this definition would not usually be regarded as a final output in their own right, primarily because of limitations in their rigor mean that they hold the potential for bias.

Gough et al. (2012) [ 19 ] suggest that the term scoping review often describes a more rapid, and so usually non-systematic, approach to describing the nature of the literature on a topic area, sometimes as part of planning for a systematic review compared with a standard systematic review. It is also important to note that there are published rapid scoping reviews where streamlined methods are used, but transparency and rigor are maintained to produce quicker results for decision-making purposes. Examples of these types of rapid scoping reviews include rapid responses to policy questions during the COVID-19 pandemic [ 20 , 21 ].

An alternative view of the difference comes from Bragge et al. (2011) [ 22 ] who suggests that a scoping review is distinguished from mapping by the inclusion of research results in the description of relevant evidence, whereas maps simply describe what is there without collating and summarizing the results of the studies.

So, even where the types of products are seen as different, there is not a consistent approach in this difference. Nevertheless, understanding why they are considered different is important in considering what is lost, in terms of an apt descriptor, if the terms are amalgamated and used interchangeably.

Historical origins

One reason that the terms scoping and mapping have emerged to describe two similar methodological approaches addressing broad types of research questions lies in the academic traditions from which they derive and the epistemological foundations upon which these are built. Scoping reviews and scoping review methodological guidance [ 12 ] tends to cite the framework defined by Arksey and O’Malley (2005) [ 23 ] and later enhancements by Levac et al. (2010) [ 24 ]. These approaches have their roots in sociological sciences. In contrast, the term evidence mapping was first used by Katz et al. (2003) [ 25 ] and has roots in the natural sciences. This was the term adopted by the EPPI Center in an early publication of a mapping review and is the term used by the Center for Environmental Evidence for the environmental sciences. The approach to evidence mapping accompanied by a visual evidence and gap map has been developed by several agencies (see Saran and White, 2018) [ 26 ], most notably by the International Initiative for Impact Evaluation (3ie) [ 27 ] in the field of international development and subsequently adopted and adapted to a wider a range of sectors through the Campbell Collaboration. These include, for example, transport [ 28 ], youth violence, disability (Saran et al. [ 29 ]), employment (Campbell et al. [ 30 ]), and health and elder abuse [ 31 ] (Table 1 ).

Suggested approaches for distinguishing between mapping reviews and mapping reviews with EGMs and scoping reviews

The emergence of two terms (scoping and mapping) to describe approaches that have much in common in terms of their objectives and methods suggests that the terms used will be shaped more by the academic background of the researcher than by inherent differences in the approaches.

Currently, as we have shown, there are many instances where “mapping and scoping” are used interchangeably. We argue, in this paper, that while there is considerable overlap between these approaches, there is value in creating a distinction between scoping reviews, mapping reviews, and evidence gap maps. They also could be considered complementary, and a review may have elements of both “mapping” and “scoping.” Each approach, within this family of “broad approach and exploratory reviews” however has a shared objective which is to overview a wider research/topic area, rather than to address a tightly focused question. The methods thereafter diverge in part to address the nature of the research question, the research objectives, the topic area, the depth required for the data extraction, and the expertise of the review team.

We propose that a useful distinction is to see mapping, scoping, and EGMs sitting within the same family of types addressing broad questions but sitting on a spectrum in some of their underpinning epistemologies, concepts, and hence objectives (Fig. 1 ).

This is illustrated in the figure below:

The Big Picture review family (commonalities and differences in approaches)

Scoping review

These review types have been variously defined and described in the literature as described above. To address the confusion in this field, a recent formal definition of scoping reviews has been proposed, describing scoping reviews as follows:

It is a type of evidence synthesis that aims to systematically identify and map the breadth of evidence available on a particular topic, field, concept, or issue, often irrespective of source (i.e., primary research, reviews, non-empirical evidence) within or across particular contexts. Scoping reviews can clarify key concepts/definitions in the literature and identify key characteristics or factors related to a concept, including those related to methodological research [ 32 ].

They can be more exploratory than mapping reviews and EGMs, not requiring an a priori set of codes in order to describe data and may draw upon a range of sources of information (i.e., primary research, reviews, non-empirical evidence) within or across particular contexts. The approach can be more iterative, inductive, or deductive [ 32 ]. The nature of the “cataloging” and coding may be in response to what is found within the literature or using pre-defined categorization codes. Scoping reviews can also be used to identify concepts and clarify terms in the literature. In contrast to a mapping review where the process of coding is predefined. Within a scoping review, the data extracted may be textual and descriptive, allowing for example an analysis of concepts and categories using simple content analysis. It may include both predefined coding and also exploration of themes (for example, Kelly-Blake et al. 2018 [ 33 ]). In contrast, along a continuum, mapping reviews will address broader questions, use predefined coding, and adopt less in-depth data extraction.

Mapping review

Mapping reviews are also a transparent, rigorous, and systematic approach to identifying, describing, and cataloging evidence and evidence gaps in a broader topic area. They are to collate, describe, and catalog the available evidence relating to the question of interest [ 18 ]. They aim to answer the question “what do we know about a topic,” or “what and where research exists on a particular area.” A mapping review typically extracts only descriptive information about the studies and applies predefined codes (high level data). In this sense, they may be informed by an “aggregative” logic. A mapping review may or may not be accompanied by an EGM but provides visual summaries in the form of tables and graphs within the text [ 36 ]. These types of reviews may well have broader focus than a scoping review, with more limited data extracted from the included papers.

Evidence and gap maps

Evidence and gap maps are described as “a systematic presentation of all relevant evidence of a specified kind for a particular sector, sub-sector, or geography”. Evidence and gap maps (EGMs) are a systematic evidence synthesis product which displays the available evidence relevant to a specific research question. EGMs consist of primary dimensions or framework (rows and columns) and secondary dimensions or filters, enabling exploration of the map using a particular focus (e.g., looking at particular populations or study designs). It creates a visual, web-based, and interactive output [ 34 ].

This type of evidence synthesis generally uses a deductive approach with a pre-specified framework to classify the data and identify gaps in the literature. However, if no suitable framework is available, then the research team can develop their own by drawing on the range of resources, such as strategy documents, policy document, and funder reports. This is one of the major differences between mapping with an EGM review and scoping reviews (for the latter, an inductive or deductive approach may be used to identify relevant data elements so the framework for classification of the data and identification of gaps does not need to be pre-specified). Evidence gap maps may accompany a mapping review as a visual representation of the included studies or can stand independently from an accompanying mapping review.

All three of these approaches are characterized by seeking to address a broader topic area rather than a specific intervention or exposure. They are an appropriate tool if the research question is one in which multiple dimensions need to be considered, for example, multiple interventions, outcomes, or types of evidence. They do not aim to synthesize data but rather describe, categorize, and catalog findings. They aim to do so by applying defined methods to ensure transparency and rigor in the process of identifying, screening, data extraction, and interpreting findings. By addressing a broad topic area these approaches support the following purposes [ 3 ]:

Knowledge generation to support broad research questions and objectives such as the following:

What types of evidence are available in a given field?

How are concepts or definitions used within the literature?

How and where research is conducted on a certain topic?

The type of broad research question will inform the choice of approach. Scoping reviews are more likely to address open questions and the concepts may be emergent such “how is a key term used within the literature,” in contrast a mapping review may address more closed questions such as “how often the key term is used within the literature and within which population groups.” An evidence gap map will similarly address a closed question, for example, “is the term used in the following types of population group: children, adolescents, older people, and people with chronic conditions.”

Scoping reviews can provide an approach that allows exploration and clarification of key concepts and definitions within the literature, as well as how research is undertaken. As this approach does not require predefined categories, it allows for more descriptive data extraction. Often the question will be narrower than in a mapping review, allowing a greater depth of exploration of the included studies.

These approaches enable a better understanding is gained of phenomena by seeing it within a wider context. Olson et al. 2021 [ 37 ] uses the allegory of the blind monks who examine the elephant, where close inspection of one part of the whole means that meaning is lost. A complete picture is needed to really understand what the elephant is. It is clear, when seeking to operationalize what is meant by a “broad” topic area that perspective matters. For a cell biologist, the cell nucleus might be a broad topic, which a single country might be too narrow a perspective for the geographer. Understanding this unique feature of “Big Picture” reviews is perhaps easier when seen in contrast to the approach used in a systematic review examining the effectiveness of a single intervention. A Big Picture review question will look at multiple interventions or exposures and multiple outcomes or effects, seeking not to synthesize but to describe (Table 2 ).

To provide a foundation for guiding future research priorities and decisions by identifying available evidence and gaps in research

Mapping reviews and EGMs incorporate a framework that is generated during development of the protocol—it is this framework which guides the development of the data extraction tool or coding tool. This framework becomes the “map” against which existing evidence is plotted.

Identifying research gaps is often a stated part of all types of research; indeed, implications for “research and practice” are an expected part of all health and social care-related research. Identifying research gaps is often a primary purpose of scoping, mapping, and mapping reviews with EGMs more than other types of review design. In particular, mapping reviews with or without evidence gap maps address this purpose with a transparency and rigor that is unique.

Evidence and gap maps aim to enable evidence to be located, both by showing what is there but also in demonstrating knowledge gaps. In order to identify knowledge gaps, an EGM begins by developing the framework against which the evidence is plotted. The development of the framework adheres to the following principles. Firstly, it may be constructed using an existing, widely accepted international typology for either interventions, exposures, or outcomes. Secondly, if no suitable framework is available then the research team may draw on a range of resources including consultation with stakeholders and relevant published theories to ensure the comprehensiveness of the framework. Without such a structure, the gaps are not identified in a systematic way, but rather inferred and chosen by the review authors (no doubt well informed) but nevertheless influenced by their own perspectives and bias. This may be particularly apparent where a review is undertaken to pave the way for further primary research by the same team. Review teams could be strongly invested in identifying their own planned research as the “research gap.”

Evidence gap maps are a systematic approach to identifying the evidence and in particular—its gaps. No other review methodology has developed a systematic approach to identifying gaps in the evidence with this level of rigor and transparency. A limitation of the approach is that it only charts what is known and does not allow a more exploratory approach that may be employed in a scoping review.

Mapping and mapping reviews with EGMs aim to describe the state of evidence for a question or topic. The review questions may therefore be open framed and broad. However, the question can be close framed and narrow. Key elements of the question can be formulated by a framework such as PO (population, outcome). For an EGM, the objectives are formalized in the framework which defines the scope of the map [ 34 ].

To inform policy decisions, where an overview of an area may be more helpful than specific questions about specific types of interventions

Mapping (with or without an EGM) and scoping reviews often have pertinence for policy makers as they are able to cover the breadth of science often needed for policy-based questions; however, it needs to be remembered that the mapping approaches do not synthesize the findings and not include quality or risk of bias appraisal. These factors may limit their value to support some types of policy decisions. However, a mapping review with an accompanying EGM can take users to the research papers and facilitate the ready location of relevant evidence. An EGM can take users to the research papers and facilitate the ready location of relevant evidence. One example has been the use of a country evaluation map used by the Office of the Prime Minister of Uganda to identify studies to inform policy work [ 38 ]. Similarly, scoping reviews can inform policy and further research through identifying the available literature pertaining to a particular topic, along with clarifying key concepts and definitions.

As a stepping stone to building the evidence architecture

Evidence mapping and EGMs may be used as a first step towards the generation of evidence-based decision-making products, such as guidance, checklists, and online decision-making tools [ 39 ]. Maps will identify the (i) existing reviews which are suitable to use a basis for guidance, etc., (ii) where there are clusters of primary studies but no review so reviews may be commissioned in priority areas to inform guidance, etc., and (iii) important policy areas in which evidence is missing. To serve this purpose, the map should be regularly updated (maintained).

While the literature is inconsistent in its definitions of these types of reviews, and different reviews use different terminology to describe methods that appear very similar, many of these differences reflect the different research traditions and adoption of terms within organizations undertaking these types of syntheses. We argue that there is value in having these distinct terms to describe the different approaches within this family of broad review types. Scoping reviews allow a more inductive, in-depth approach with, including fewer included studies and a greater level of data extraction compared with mapping reviews. Mapping reviews and evidence gap maps address more closed questions, with pre-specified items defined and code-able when contrasted with scoping reviews. Evidence gap maps offer a visual, interactive output for users to locate evidence. The predefined framework offers a rigor to locating gaps in the existing literature and displaying these differences which is unique to these approaches.

This proposed new “Big Picture” review family within evidence synthesis contributes to the wide array of possible approaches to synthesizing literature. This multitude of choice presents challenges in selecting the correct evidence synthesis methodology. One tool that has been developed to assist in the appropriate selection of a method is the “right review” tool ( https://whatreviewisrightforyou.knowledgetranslation.net/ ). The tool enables researchers to answer a series of simple questions regarding the type of research questions they are undertaking for their review and selects an appropriate type of review based on their answers to the questions. The tool currently includes 41 different types of evidence synthesis methods [ 40 ].

A recent development has been changes made to the SR Toobox ( http://systematicreviewtools.com/index.php ) to include searching for tools to support different review types, as well as for different stages of the review. The Big Picture review family is increasingly well supported by methodological guidance and automation tools to support the process of undertaking high quality systematic reviews.

The existing guidance for the conduct and reporting of scoping reviews also applies to mapping reviews (JBI). Further development is needed in the methods of preparing a coding framework, particularly when the mapping review will also include the development of an interactive EGM. Current models of good practice exist; however, current guidance and reporting standards are limited.

This commentary details and describes some of the broad approaches within the evidence synthesis toolkit, specifically scoping reviews, mapping reviews, and EGMs. We have identified similarities and differences, based on our expert experience, between these reviews. We propose grouping them as a family of evidence synthesis to address broad research question and objectives. In so doing, we advocate that adherence to the principles of rigor and transparency that give users of evidence synthesis confidence in the reliability of the results of the review.

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Acknowledgements

Andrea Tricco is funded by the Tier 2 Canada Research Chair in Knowledge Synthesis.

Zachary Munn is funded by an NHMRC Investigator grant APP1195676.

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FC and HW conceived the idea for the paper, and FC initiated the initial draft. HK, AT, HW, ZM, AS, and AS contributed to the comments and edits of subsequent drafts of the paper. HK and FC are co-chairs in the NAVIGATOR method group and took a lead in the preparation of this work. The final manuscript has been read, edited, and agreed by all the contributing authors.

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The original online version of this article was revised: The authors identified an error in the author name of Zachary Munn and Danielle Pollock and affiliation of Fiona Campbell. The incorrect author names are: Zacchary Munn, Dannielle Pollock corrected to Zachary Munn, Danielle Pollock and affiliation 2 has been removed from author Fiona Campbell.

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Campbell, F., Tricco, A.C., Munn, Z. et al. Mapping reviews, scoping reviews, and evidence and gap maps (EGMs): the same but different— the “Big Picture” review family. Syst Rev 12 , 45 (2023). https://doi.org/10.1186/s13643-023-02178-5

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• 6th IET GCC Robotics Challenge 2022 by Engineering
• Seminar on Electricity Hazards by Engineering
• UTAS - Ibra students participated in the Annual TechFest2022 by Information Technology
• IEEE 3rd SYP Congrees 2022 by Engineering
• A Successful Presentation at DU First Undergraduate Student Poster Competition by Engineering
• ICEC holds an Industrial visit at Oman Telecommunication Company, Muscat by Engineering
• جامعة التقنية و العلوم التطبيقية بابراء تخرج اكثر من الف خريج و خريجة ... by Educational Technology Centre
• ELC held a Potluck Lunch Party by English Language Centre
• Writing Research Proposal by Business Studies
• Course Project Orientation by Information Technology
• Senior Project Orientation by Business Studies
• Renewable Energy System Modelling and Installation Online Workshop by Engineering
• Recon: Student-Centered Learning Workshop for Engineering Staff by Engineering
• College Policies Awareness Webinar by Engineering
• Exploring Python Programming for Mathematical Application by Information Technology
• Community Outreach Program - Workshop on Computer Hardware Servicing by ICEC
• Introduction to Robotics, Mechanical Assembly and Robot C Programming by Engineering Department
• Community Outreach Program – Solar-Powered Pumping System Webinar by Engineering Department
• Basic Arduino Programming and Interfacing Online Workshop for Students by Engineering Department
• Approaches to Increase Scientific Publications in Highly Reputed Journals by Business Studies Department
• Workshop on PV System Design & Implementation to Domestic Load by Engineering Department
• Awareness seminar on General Electrical Safety by Engineering Department
• English Society Celebrate Oman's National Day by English Language Centre
• Workshop on Developing Practical Skills Using DBMS Software for Computer Engineering Students by Engineering Department
• UTAS - Ibra Student Attended Huawei ICT Skill National Final Examination by IT Department
• Specialization Orientation Program by BS Department
• "Ascend Yourself, the Bottom is Crowded" by IT Department
• تمويل 13 بحثاً علمياً في جامعة التقنية والعلوم التطبيقية بإبراء by Administration
• UTAS - Ibra Student Qualified for the Huawei ICT Skill Competition by Information Technology
• UTAS - Ibra students attended the Oman Collegiate Programming Competition by Information Technology
• Health Safety Environment Committee by Information Technology
• UTAS - Ibra Students took the Huawei ICT Skill Exam by Information Technology
• English Language Centre Writing Centre Commencement and Invitation to Teach by English Language Centre
• IEEE Online Campaign for AY 2021-2022 by Engineering
• "Be Faster and Smarter at Work" by Business Studies
• Data Cleaning and Validation by Business Studies
• Bridging the Gap between Academia and Industry by Business Studies
• HSE Induction Program for New Engineering Staff by Engineering
• New Students Induction Program by Business Studies
• Live Webinar on Introduction to Materials by Engineering
• Project Orientation on Senior and Graduating Students by Business Studies
• Workshop on Writing Research Proposal by Business Studies
• A Webinar on "AdTrac - Counselling - Guidelines to Advisors" to Engineering Advisors by Engineering
• Transformation of Engineering Education by Engineering
• Staff Webinar on Stress - A Powerful Driving Force, Not an Obstacle by Engineering
• Engineering Hosted Research Methodologies Webinar by Engineering
• Online Course Project Orientation by Information Technology
• ELC celebrated Semester 1- Opening Lunch by English Language Centre
• البرنامج التعريفي للطلبة الجدد 2021-2022 by Administration
• Engineering Online Discussion Forum Based on Synergizing Clean Energy and Green Transportation for Smart Cities by Engineering
• Awareness Program - Advising and Registration by Business Studies
• Engineering's Dr. Shamganth K Joins the Elite Rank of IEEE Senior Member by Engineering

AY2020-2021

• Webinar on Building Mobile Robots and Arduino Based Robot Assembling and Programming by Engineering
• IT Department Awarding Day 2021 by IT
• Webinar on 'Scalability Challenges in IoT - Edge Computing, Block Chain and Industry Revolution 4.0' by IT
• Entrepreneurial Opportunities in Omani Market Webinar by Business Studies
• New Students' Induction Program by Business Studies
• مؤتمر علمي يستعرض تقنيات الثورة الصناعية الرابعة بإبراء by Administration
• IEEE UTAS - Ibra Student Branch Conducts IEEE Membership Campaign Online by Engineering
• Engineering OJT Trainees' Final Presentation: Appraised by External Examiners by Engineering
• HSEC at ELC conducted talk series for staff and students in the month of March, 2021. by English Language Centre
• Engineering Students Virtual Training on Network Modeling and Simulation using OPNET Riverbed Modeler by Engineering
• Engineering QA Awareness and Active Participation in the Committee Work Webinar by Engineering
• Entrepreneurship Unit Hosted Webinar entitled 'Entrepreneurship and Innovation Camp' by Engineering
• Two-Day Electrical Skills Enhancement Workshop for Engineering Students by Engineering
• Training in Computer Network Configuration and Installation by Engineering
• A Virtual Industrial Tour to Telecommunication Regulatory Authority by Engineering
• Introduction to Raspberry Pi Webinar for Engineering Staff by Engineering
• Effective Use of Autodesk Inventor Professional Engineering Program in Online Teaching by Engineering
• Diabetes Mellitus Awareness Program Conducted for Engineering Staff by Engineering
• Engineering Alumna Speaks on a Webinar entitled 'Passion of Artificial Intelligence of Things' by Engineering
• 2nd INNOVATIA 2021 by Business Studies
• IT Department’s Workshop with PDO by Information Technology
• Engineering HSE Committee Went Virtual on Fire Extinguisher Training by Engineering
• Engineering Department Hosted Webinar on Project Management Skills Required for Administrative & Technical Professionals by Engineering
• Workshop on Photovoltaic System Design and Installation by Engineering
• Hands On Training on Packet Tracer by Engineering
• Engineering Department hosted a Webinar on "Latest Mobile Technologies" for OJT & Prospective Graduates by Engineering
• Engineering Hosted CNC Programming and Fusion 360 Manufacturing Webinar for Mechanical Engineering Staff by Engineering
• IT STAFF AND STUDENTS PRESENTED PAPERS IN INTERNATIONAL CONFERENCE by Information Technology
• Google Hash Code Programming Competition by Information Technology
• A Talk on MS-Project Application in Course Project by Information Technology
• Webinar on "Arduino Programming and Interfacing" by Information Technology
• IEEE- UTAS-Ibra Student Branch Hosted a National Wide Webinar on "Introduction to Deep Learning" by Engineering
• Workshop on Literature Review by Business Studies
• WORKSHOP ON HOW TO FIND INNOVATIVE IDEA by Business Studies
• Webinar on "Review of Literature & Referencing" by Information Technology
• BlockChain Technology by Information Technology
• Report on Senior/Graduation Project Orientation by Business Studies
• Management Research using the Analytic Hierarchy Process (AHP) Technique by Business Studies
• Case Development and Writing by Business Studies
• Risk Management Information System Awareness Program for Engineering Staff by Engineering
• Staff Lunch Treat by English Languge Centre
• External Examiners from Various Industries for Engineering Final Project Evaluation by Engineering
• Building a Culture of Participation by ETC
• Awareness on Common Password Threats by ETC
• National Speech Contest by ELC
• ‘Teaching Writing Using Internet Tools’- Webinar by ELC
• Webinar on Occupational Health and Safety by ETC
• Staff of the Month Awarding Ceremony by ELC
• IT Students Graduation Project in Final Round of Upgrade by IT
• UTAS-Ibra Students compete in Speech Contest by ELC
• Awareness on Staff Related Policies for ETC Staff by ETC
• Engineering hosted a 'Network Modeling and Simulation using OPNET' Online Workshop by Engineering
• Higher Education & Industry Symposium – Bolstering Connection Towards Oman 2040 by Engineering
• IEEE – Ibra bagged the MOST ACTIVE STUDENT BRANCH AWARD in Oman by Engineering
• Induction Program for New Intake Students by IT
• Inspiring Students Through Alumni Experience by IT
• Policy Awareness Webinar by Engineering
• Engineering Students Take Part in 'HUAWEI ICT COMPETITION MIDDLE EAST 2020' by Engineering
• Incentive Methods by Business Studies
• Methods in Training and Development by Business Studies
• National Day Celebration by Engineering
• نظرا لأهمية غرس قيم المواطنة الحقيقية و تنمية حس المسؤولية المجتمعية بين by Admin
• Specialization Orientation program by Business Studies
• Business Quiz by Business Studies
• Research Questionnaire Preparation by Business Studies
• WORKSHOP ON RESEARCH METHODOLOGY FOR GRADUATE PROJECT by Business Studies
• Engineering Alumna Speaks on a Webinar Entitled "How Course Projects and Internship Programs Support the Recruitment Procedure of Scholars" by Engineering
• Workshop on Curriculum Development and Review Framework by Business Studies
• Webinar - New Features of ADTRAC by Engineering
• Financial Modeling Using Excel Workshop by Business Studies
• ETC organizes Webinar on ProQuest Databases and Turnitin by ETC
• UTAS-Ibra Conducted Its First Ever Online Examination with ETC Technical Team by ETC
• Live Webinar: Importance of Soft Skills & Personal Branding by Engineering
• Live Webinar: The significance of Omani Graduate achievements in the reality of work by Engineering
• Induction Program to New Students by Business Studies
• Intelligent Electric Vehicle Charging System by Engineering
• Smart City Development through IoT by Engineering Department
• Role of the Smart Grid in Facilitating the Integration of Renewables by Engineering
• "EMERGING DESIGN AND TECHNOLOGIES IN ENGINEERING Internet of Things (IoT) & MICROSTRIP ANTENNA" by Engineering
• Artificial Intelligence for Business Operations by Engineering Department
• 5G Live: Webinar – "Get in-depth knowledge about future Generation Technology and designing of 5G business strategy" by Engineering
• An Online Live Seminar on 'Adopting Green Marketing Strategy and its relation to Production Cost in Industries' by Engineering
• Exploring the Rule-based Expert Systems for Smart Healthcare in 21st century by Engineering
• Making an effective Video lecture - Use of Different Tools and Software by Engineering
• Webinar on the Challenged Experienced by Young Entrepreneurs: Strategy to Way Forward by OJT
• Audit Committee Overlapping and Forward-looking Disclosure: An Untold Story of Omani Financial Institutions by Business Studies
• Online Seminar on EMI/EMC technologies for Industrial IOT Platform by OJT
• Webinar on Smart Grid by Engineering
• Webinar on Strategies for an Entrepreneurial Career by Business Studies
• Automotive Safety Technologies by Engineering
• Condition Monitoring of Transformers Using Dissolved Gas Analysis Techniques by Engineering

AY2019-2020

• Webinar on "Augmented Reality Using Unity Engine & Vuforia" by IT
• Webinar on Thinking Skills and Problem Solving by IT
• Workshop on Data Analysis vs Data Analytics by IT
• Workshop on Quality Awareness by IT
• IT Students Presented Papers in SNSIR4.0 Webinar, HCT, Muscat by IT
• Math Lessons in GeoGebra with Moodle Integration by IT
• External Examiners from various HEI’s for Engineering Student’s Course Project Evaluations by Engineering
• ETC Goes Online Training/Courses by ETC
• Development of Practical Skills in the use of DBMS Software by Engineering
• 8th Annual Programming Competition by Engineering
• Hands on Training in Packet Tracer by Engineering
• Workshop on Mathematics using Apps, Software and IT Technology by Information Technology
• IT Students Awarding Day by IT
• Engineering students Won Second place in Robotics Challenge by Engineering
• Parents’ Perceptions on Graduate-Children Choosing Entrepreneurship as their Career by Business Studies
• Teachers’ Day Celebration at ELC by ELC
• Poster presentation for 16th International Gas Research Conference (IGRC 2020) hosted by Oman LNG by Engineering
• Questionnaire Preparation Workshop for Senior/Graduation Project Students by Business
• Workshop on Literature Review and Referencing for the Senior/Graduate Project by Business
• Ericsson Oman L.L.C, Muscat – Guest Lecture by Engineering
• Dr. CK Chairs a Session and Presents a Paper at SQU’s 4th International Conference on Language, Linguistics, Literature, and Translation by IT
• Configuring Cisco IOS using Python by IT
• Al Omran Private School Community Outreach Program by IT
• Guest Lecture on Generator and it's Protection by Engineering
• Innovative Idea Poster Presentation by Business Studies
• Does Gamification Enhance Learning Experience of Accounting Courses? – An Experimental study at Ibra College of Technology by Business Studies
• Engineering students educational field trip to Sultan Qaboos Port,Muscat by Engineering
• Strategic Plan 2019-2024 Awareness by ELC
• Workshop on SCL Tools by Business
• Risk Management Approach in Curriculum and Program Quality Improvement by IT
• Business Department Inducts New Students by Business
• Business Department Conducts Senior/Graduation Project Orientation by Business
• Senior/Graduation Project Workshop on Microsoft Word Preparation by Business
• Toastmasters Speaking Workshop by ELC
• Workshop on Innovative Idea Generation by Business
• Strategic Plan- 2019-2024 Awareness Program by Business
• Course Project Orientation by IT
• IQAC-Strategic Plan 2019-2024 Awareness Workshop by IT
• GFP Common Quality Audit Portfolio And Quality Audit Visit Awareness Workshop by ELC
• Academic Advising and Improvement Action based on Student’s Registration Feedback by IT
• Reviewing and Developing Curriculum of Electrical and Electronics Engineering Workshop by Engineering
• IEEE Annual Gathering in Oman by Engineering
• ELC Held A Semester End Buffet Lunch by English Language Centre
• Electrical Machine Testing and Wiring Design Workshop by Engineering
• ICT Staff Attend 'ACT IP DAY' by IT
• Dean's Honor List by ELC
• ICT SKILLS COMPETITION 2019 CONCLUDED by IT
• Technology Integrated in English Language Teaching by ELC
• Omanisation Lecture by Business Studies
• Industry Visit HIGH TOWER GROUP OF COMPANIES by Engineering
• Industry Visit to ENGIE STOMO by Engineering
• Field Study Visit Munisifeh Ruins by Engineering
• Mathematics Challenge Battle 1 by Information Technology
• Training on Total Station by Engineering
• Network Modeling and Simulation by Engineering
• Use of Microsoft Office Workshop by ELC
• Speech Competition Day by ELC
• Peer Tutoring Workshop by ELC
• ELC Celebrated 49th National Day by ELC
• Integrity Day at ELC by ELC
• Industry Visit to Omani Securities Association by Business Studies
• Workshop on SPSS by Business Studies
• Field visit to The Chedi Hotel by Engineering
• تقرير محاضرة ( قانون العمل العماني ) Lecture Report (Oman Labor Law) by Business Studies
• Industrial visit Haya Water Muscat by Business Studies
• HVAC and Building Services study tour at Mohammed Al Ameen Masjid, Muscat by Engineering
• ICT Skills Competition 2019 Elimination Round by IT
• Engineering students selected as Panelists for Robotic Competition for School students by Engineering
• 49th National Day Celebration of Engineering Department by Engineering
• Community Engagement Program - National Day Celebration at Al-Kamil Power Station by Engineering
• Community Service at Al-Wafa Social Center by IT
• Academic Advising Workshop by Business
• Development of Practical Skills in the use of DBMS software by Engineering
• CNC Programming On Fanuc Control by Engineering
• Research Through Student Projects by Engineering
• Academic Counselling for Students by Business Studies
• WORKSHOP ON BEARING MAINTENANCE AND LUBRICATION by Engineering
• Specialization choice induction program for SPRING 2020 by Engineering
• Workshop on ‘Microsoft Excel’ by Business Studies
• Engineering students Industrial visit to Power Station, Alkamil by Engineering
• Employers Recommended Training Program on PSTN Modeling and Simulation to Telecommunication and computer students by Engineering
• Workshop on Entrepreneurship by Business
• Health and Safety Awareness by Business
• Regional Final Exam for Huawei ICT Skills by IT
• Omani Women’s Day Celebration by Business
• Hands on Training in Packet tracer by Engineering
• Cooperation Agreement between Ibra College of Technology and Omani Society for Education Technologies by Administration
• IT Students won 3rd Prize in SITAM 2019 by IT
• ICT Graduation Ceremony 2019 by Administration
• Microsoft Word Presentation Workshop by Business
• Questionnaire Preparation Workshop by Business
• IT Students attend Huawei ICT Skill Workshop by IT
• Global Careers In Cyber Security – The Importance Of Skills And Education by IT
• Health and Safety Awareness Program by Engineering
• Policy Management Portal Workshop by IT
• Enhancing Blended Learning Workshop by IT
• Academic Advising by IT
• Robotics Workshop by Engineering
• Community Outreach at Al Omran Private School by IT
• RMC conducts Risk Management Planning for ICT Staff by QA
• Industrial Visit to OMANTEL Ibra by Engineering
• Engineering students Industrial visit to Oman Fiber Optic Company SAOC Muscat by Engineering
• Training Program on 'Computer Hardware Servicing' by Engineering
• 3D Modeling Workshop by Engineering
• Training program on Computer Network Administration by Engineering
• A Talk on 'Hands on Security' by IT
• Basic Electronics Skill Development Workshop by Engineering
• Review of Literature & Referencing by Business
• ICT Alumni View On Exploring Career in Electrical Power Plant Engineering by Engineering
• Workshop on Writing Research Proposal by Business
• IP Addressing and Subnetting Student Workshop by IT
• Cooperation Agreement between the Ibra College of Technology and the Oman Chamber of Commerce and Industry, Ibra by Administration
• IEEE Campaign by Engineering
• ELC conducts Policy Awareness Program for staff by ELC
• Job Search Technique Presentation and Training Orientation by OJT
• Teaching and Learning Workshop by IT
• ELC conducts an 'Induction Program' for New Intake Students by ELC
• Memorandum of cooperation was signed between Ibra Technical College and Muscat College by Administration
• ELC Staff Gathering by ELC
• ELC conducts Flipped Classroom Using Edpuzzle Training by ELC
• Induction Program for new intake by IT
• Workshop on 'ISA Report Writing' by IT
• A talk on 'CLASSROOM ASSESSMENT TECHNIQUES' by IT
• Academic Advising Workshop by IT
• A talk on 'Augmented Reality' by IT

AY2018-2019

• ELC Year-End Get-to-Gather by ELC
• Alumni Workshop on CV Writing by Business
• Report for the workshop "Recent Trends in Accounting" by Business
• Alumni workshop on "Fundamental Analysis" by Business
• Student Appreciation Day 2019 by Business
• ICT Business Studies’ Benchmarking with Muscat College by Business
• Academic Counselling for Students by Business
• Engineering Students Awarding Day 2019 by Engineering
• Reimagining Teaching and Learning in Higher Education by Business
• IT Student Awarding Day 2019 by IT
• Center for career guidance Department in coordination with the Department of Engineering Organized Mock Interview & Motivational Talk to Prospective Graduates by Engineering
• How to Use the Voice Recorder for the Speaking Exam by English Language Centre
• Report on Guest Lecture – Functions of Human Resource Management by Business Studies
• Specialization choice induction program by Engineering
• Specialization Orientation Program by Business Studies
• HCT benchmarks ICT’s Staff Performance Appraisal System by Educational Technology Centre
• Alumni Motivational Talk Series by Engineering Department
• Review of Literature & Referencing by IT Department
• Benchmarking between Engineering Department of Ibra College of Technology and Nizwa College of Technology by Engineering Department
• IT Students at Oman Data Park by IT Department
• Memorandum of Cooperation with Bahwan Veolia Water Desalination, Sur by IT Department
• Students Participation in an International Conference by Business Studies Department
• Community Outreach Program by IT Department
• Accounting Students Participation in a Research Conference Organized by Arab Open University, Oman by Business Studies Department
• Session Chair in an International Research Conference by Business Studies Department
• Presentation on Student Request System by IT
• IT Staff Attended 2nd Academia And Industry Meeting Workshop by IT
• IT Students at Oman Netacad Student Day 2019 by IT
• IT Students Presented Papers at AOU-ISRC 2019 by IT
• IT Students Presented Papers at CICTAB 2019 by IT
• English Language Teaching Professional Development Workshop by ELC
• Workshop on Digital Marketing by IT
• Engineering-Alumni-as-Industry-Expert-Panelists by Engineering
• ICT Risk Management Committee meets SQU Risk Management Team by RMC
• OJT Department Benchmarking with Nizwa College of Applied Science by OJT Department
• Guest Lecture – Management Accounting II by Business
• Telecommunication Students Final OJT Presentation at Omantel by Engineering
• Ibra College of Technology in Observance of Earth Hour by ETC
• College OJT Orientation Program by OJT Department
• Art of Model Making Competition by Engineering
• Advanced Training on CNC by Engineering
• ELC Staff attend the 2nd Sohar University TESOL Symposium by ELC
• ELC students attend the Open Day at Shinas College by ELC
• Critical Thinking Workshop by ELC
• Mathematics Challenge 2019 by IT
• Practicals on Fundamentals of Computer Security by IT
• ICT Innovatia 2019 by Business
• Guest lecture on "Digital forensics" by IT
• Familiarization of Practical Antenna Systems by Engineering
• Innovatia 2019 by Business Studies
• Engineering Robotics Team Wins 2nd Place by Engineering
• Health and Safety Exhibition by Engineering
• Integrated Petroleum Services Plant Visit by Engineering
• Employee Recruitment And Compensation Practices by Business
• ICT Networking Competition–2019 by IT
• A Talk on Free & Open Source Software (FOSS) by IT
• Using Turnitin in Moodle by IT
• Fiesta Mathematica 2019 by IT
• Community Outreach Program by Engineering
• 7th Annual Programming Competition by Engineering
• Students Specialization Meet by IT
• Educational Tour at Oman Convention and Exhibition Centre by Engineering
• IEEE-ICT Students Shine in IEEE Oman Congress 2019 by Engineering
• ELC Celebrates Teachers' Day by ELC
• Industry Exposure for Bachelor of Computer Engineering Students by Engineering
• Collaboration with Public Authority for Consumer Protection by Business
• An Industrial Visit to OMANTEL, Ibra by Engineering
• PLANT VISIT in ENGIE STOMO Company by Engineering
• National Museum Visit by ELC
• Engineering Students Visit Oman Fiber Optic Company by Engineering
• Towards Spreading the Culture of Research and Innovation by Business Studies
• Workshop on Questionnaire Preparation by Business
• ELC Conducts Policy Awareness Meeting by ELC
• ELC (IQAC) Reviews the Spot Audit Checklists by ELC
• MEMS Energy Harvester (Engineering Lecture Series) by Engineering
• Industrial Visit to Sohar Aluminum by Engineering
• Senior Project Workshop on Research Methodology by Business Studies
• Senior Project Workshop on Manchester Phrase Bank and Literature Review by Business Studies
• Senior Project Workshop on Writing Research Proposal by Business Studies
• Seminar on Visualization of Temperature Distribution during Real Time Multiphase Flow Process in Various Applications Docs by Engineering
• Induction Program to New Students Docs by Business Studies
• Workshop on Google Docs by ETC
• Induction Program for new intake IT students by IT
• Seminar on Project Based Learning by IT
• A talk on "Network OS Administration & Security" by IT
• Workshop on Entrepreneur by Business Studies
• ETC Participated the Seminar on Legal Legislation for Women Working in the Government Sector by ETC
• Engineering Induction Program for New Intake by Engineering
• IT STUDENTS VISIT OMANTEL - Semester II by IT
• ProQuest Training by ETC
• Business Students’ participation on Agriculture, Fisheries and Food Investment Forum by Business
• IT Course Project Orientation by IT
• المكتب الوطني لنقل التكنولوجيا by Admin
• A Team of ETC System Developers Attended the Oracle Seminar at Kempinski by ETC
• مشاركة الكلية التقنية في اجتماع غرفة تجارة وصناعة عمان لمناقشة أهمية قطاع المعارض والمؤتمرات by Student Affairs Office
• Student Centered Learning using Technology by Business Department
• Students’ Project Evaluation by Experts from Industries by Engineering Dept
• Plagiarism Awareness Workshop by ELC
• Centre Staff General Meeting with New HoC by ETC
• Academic Advising - Tips & Discussion by IT Department
• Internal Project Presentation by IT Department
• Staff Gathering by IT Department
• Workshop on Vocabulary Development by English Language Centre
• IEEE-ICT Student Branch Conducts Short-Term Course on 4G Network Essentials by Engineering
• Community Engagement Activity by Business Studies
• GREEN SCARF Project Won Second Place in NAMA Architectural Design Competition by Engineering Dept
• An Industrial Visit to Al Kamil Power Station by Engineering Dept
• Engineering Department Celebrates 48th National Day by Engineering Dept
• Engineering Students Win Second Place and Fourth Place in Al Roya Youth Initiative Awards by Engineering Dept
• Probation Students Meeting by Business Studies
• MONOLITH 2018 by Business Studies
• ETC Participated in ServiceDesk Plus Workshop by ETC
• Awareness Program on Policy Management and Approved Policies for ETC Staff by ETC
• ETC Participates in ICT Open Day 2019 by ETC
• ETC Lab in-charge attend Installation and Use of Electronic Whiteboard Workshop by ETC
• ETC holds Workshop on ProQuest by ETC
• Senior Project Workshop on SPSS by Business Studies
• Engineering Students Got 1st and 3rd Prize in Invasion 2018 Competition by Engineering
• ICT Celebrates 48th Glorious National Day by Admnistration
• ETC holds Risk Management Awareness Program by ETC
• ETC staff attends Awareness Program on ISA Requirements by ETC
• Strengthening the Relationship with Alumni through Personality Development and Career Guidance Seminar by Engineering Dept
• Two Day Event - Muscat Securities Market Awareness Program by Business Dept
• Workshop on Flip Activity by Business Dept
• IT Students in Community Out Reach Program by IT Dept
• First Aid Skills Awareness Program by Engineering Dept
• CIMS Awareness Program for IT students by IT Dept
• سبع مائة و اربعة و خمسون خريج و خريجة ترفدهم تقنية ابراء الى سوق العمل by Admin
• Electrical and Electronics Measuring Instruments and Equipment Workshop by Engineering Dept
• Workshop on 'Project Poster Preparation' by IT Dept
• Induction Program for New Intake Diploma 1st Year Students by IT Dept
• Workshop on 'Assessment of Operational Plan - AY2017-2018' by IT Dept
• Industrial Visit to Bin Abdan International Consultancy Group by Business Dept
• Preparation for Examination and Concentration in Studies by Business Dept
• Community Engagement Workshop by Business Dept
• Workshop on Policy Review by IT Dept
• Linkage with Industry Promotes Partnership with Academe Through Guest Lecture on GSM NETWORK by Engineering Dept
• Staff Awareness Program on Reviewed Policies by Engineering Dept
• Training on Basic Computer Network Administration by Engineering Dept
• IT Society Students in Community Service at Al-Wafa Social Center by IT Dept
• IT Students Visit Omantel Ibra by IT Dept
• Workshop on MATLAB programming and SIMULINK modeling by Engineering Dept
• Workshop on Website Development using Wix by Engineering Dept
• Workshop on PCB Development by Engineering Dept
• IT Students Visit Oman Fiber Optics by IT Dept
• Al Roya Youth Initiative Award Awareness Program by Engineering Dept
• Report on Workshop held on 12th September 2018 by Business Studies
• A talk on "Software Methodologies and System requirement specifications" by IT
• A talk on "Course Project Orientation" by IT
• Workshop on “Review of Literature & Referencing” by IT
• Business Induction Program Semester 1 by Business Studies
• Staff Students Gathering by Engineering
• 4th Teaching and Learning Conference by ELC
• Engineering Student Gathering by Engineering
• Writing Research Proposal Workshop by Admininistration
• Workshop on Effective Project Guidance and Assessment by QA Dept

AY2017-2018

• " فقط ابتسم" حملة ينظمها طلبة الكلية التقنية بإبراء لتوزيع سلات غذائية للطلبة و الأسر المحتاجة
• الكلیة التقنیة بإبراء /حلقة عمل
• Smart Education and Technology Symposium 2018
• RMC spearheads Workshop on Incident Response Planning
• الملتقي الطلابي السابع بالكلية التقنية بعبري
• Engineering Students Got Top Awards In the Al-Roya Project Competition
• Graduation Ceremony 2017
• ICT student bagged second place in a 10-km run for higher education students
• Engineering Project Selected to Compete in the National Level of OCCI Innovation Award
• Engineering Projects Gets Nod for FURAP
• ICT purchased new PC Hardware Trainer
• An Interview with the Captain of the historic ‘Jewel of Muscat’
• The Interaction with Entrepreneurs at OCCI
• Accounting Students Participation in Research Conference
• An Interview with Mr.Hatim Al Abdissalam
• Let’s Read- The Stories of Our Ancestors
• Open Day 2017
• An Interview with the Conqueror of Mount Everest and Pumori
• 2nd Alumni Meet
• Health and Safety Workshop
• ICT students won First Place in Network Troubleshooting and Configuration
• Engineering Student Papers got accepted during 8th National Symposium on Engineering Final Year Projects
• Developing and Strengthening of On-The-Job Training Workshop
• Flipped Classroom Presentation by Dr. Azzah Ahmed Said Al Maskari
• An Interview with the Asian games medal winner Mr.Barkat Al-Harthi
• IT Networking Students Won First Place in INVENT2017
• OJT Training Orientation Seminar
• Fiesta Mathematica 2017
• Workshop on Project Development NAMA AMBASSADORS
• ICT Team visit Special Economic Zone in Duqm
• A Talk on "Smart Technologies, Security and Social Media"
• ICT Morning Walk 2017
• Guest Lecture on "Power of Mind and Self Esteem"
• ETC Team Building Activity 2017
• Business Studies student got the 2nd prize in an Intercollegiate Management Meet (Synergy 2K’17)
• ICT Conducted a Special Training Program for Young Students
• Engineering Final Project Evaluation by Industry Experts
• Engineering Robotics Team wins Second Place
• Engineering 6th Annual C Programming Competition
• Orientation Program on Professional Bodies
• Industrial Visit to OMAN FIBER OPTIC COMPANY
• Project Collaboration Meeting with Zubari Automotive Group Ibra
• Symposium on IoT and Big Data by IEEE-ICT Students and Staff Members
• Engineering Student and Staff attend Robotics Training
• Engineering Staff attends IEEE Symposium of Engineering Education (ISEEE’18)
• Engineering Department Recipient of the Renewable Energy System under Mustadeem Program
• Mechanical Engineering Students visit Desalination Plant in Sur
• Engineering conducts seminar on Student’s Centered Learning
• Engineering Department Inaugurates Professional Team
• Engineering Staff Attends "Training Program on Usage of First Aid Kit"
• Engineering Students Industrial Visit to OMANTEL
• Engineering Department Project Collaboration meeting with Mazoon Ibra
• IEEE-ICT Students Field Test Activity with TRA
• Public Safety and Evacuation Training Program
• Mechanical Students Industrial Visit to United Engineering Services (UES)
• Engineering Department Initiates MoC with Voltamp Transformer Company
• On-The-Job-Training Orientation Programme
• Engineering Staff visit Al Kamil Power Plant
• Computer Hardware Servicing and Network Servicing Workshop
• Engineering conducts workshop on 'Entrepreneurship Skills and Strategies'
• Engineering Conducts Workshop on 'Microsoft Virtual Academy'
• Architecture students visit STFA-HLG Construction Company
• Engineering-Students-Visit-Oman-Fiber-Optic-Company
• Industrial Visit to OMANTEL
• Seminar on OMANTEL NETWORK
• ELC holds "Document Management System Workshop"
• ELC RCC in ELTPDW, Ibri College of Technology
• ICT Engineering Students Project Got Among the Top Two from Sharqiyya Region
• Staff Development Program on Flipped Classroom Best Practices
• Guest Lecture to Marketing Students
• Presentation on Document Management System
• Industrial Visit to Muscat Security Market
• Workshop on Entrepreneurship
• Industrial Visit to Seeb Waste Water Treatment Plant Project
• Guest Lecture on Students Studying 2nd Year Diploma
• Senior Project Evaluation by External Examiners
• Business Studies Students Visit Central Bank of Oman
• SYNERGY-2018
• Workshop on Plagiarism Policy and Turnitin
• MSM Gathering
• Student development program on 'Co-operative and Collaborative Learning'
• Business Department Induction Program to New Students
• Business Department Probation Students Meeting
• Workshop on Final exam question paper review
• Specialization Orientation Program
• Advising and Registration Workshop
• Business Department Staff Picnic
• 47th National Day Celebration
• Industry Visit to Secretariat General for Taxation
• Industrial Visit to Central Bank of Oman
• Industrial Visit to Nabil Biscuits
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Impact of fill-in-the-nodes concept maps on low prior-knowledge students learning chemistry: a study on the learning achievements and attitude toward concept maps †

First published on 1st November 2023

Numerous studies have proven the learning benefits of concept maps in science subjects, particularly for students with low prior knowledge. There is a scarcity of research dedicated to the examination of chemistry courses at the university level, and the findings pertaining to academic performance in that subject exhibit a lack of consistency. This study examined the impact of concept maps on students of a General Chemistry course who had low prior knowledge. The study applied a quasi-experimental design to collect data on two topics: uncertainties of measurements (Topic 1) and acid–base (Topic 2). Fill-in-the-nodes concept maps were developed and served as learning materials. ANCOVA and Johnson–Neyman techniques were used to analyze the scores of concept tests of Topic 1 and Topic 2, respectively. In both Topics 1 and 2, the results showed that the treatment group outperformed the control group. However, the aforementioned finding was limited to the subset of students whose pre-test scores were below 30.7 out of a total of 47. From the analysis of the attitude questionnaire, the authors concluded that the students appreciated the usefulness of concept maps. However, they might hesitate to engage in using this new learning tool. The study's findings strengthen the evidence of the learning benefits of concept mapping. Moreover, using concept maps in teaching is feasible because of their low cost and minimally invasive modification to instructional design. The practices for implication of concept mapping are also discussed.

Introduction

Students with low prior knowledge seem to face challenges in learning chemistry. According to Ausubel's assimilation theory of learning ( Seel, 2012 ), students build up their knowledge through prior knowledge (background knowledge), or what they have learned previously. Students always bring to the classroom their existing concepts about the nature of the world. If these concepts are incorrect or inconsistent with true science principles, they will interfere with and create barriers to learning new concepts. The levels of prior knowledge correlate with the comprehension of scientific texts ( Best et al. , 2004 ). Students with low prior knowledge have a diminished capacity to comprehend and employ chemical understanding due to their limited repertoire of foundational concepts, hence impeding their ability to build novel knowledge. According to the interactive compensation model of learning, three predictors of students’ learning in chemistry are cognitive ability, prior knowledge, and motivational beliefs. Among these predictors, prior knowledge is the most important factor influencing learning outcomes ( Crippen et al. , 2005 ; Crippen and Brooks, 2009 ; Seery, 2009 ).

Concept maps have been recognized as powerful learning tools that have received substantial attention in science education research for enhancing the learning outcomes of students with low prior knowledge. Concept maps can serve as scaffolds for cognitive processing. Students with low prior knowledge may benefit most when learning with concept maps because they could retrieve a more central understanding than learning with texts ( O’donnell et al. , 2002 ). Chu and colleagues (2019) indicated that with the assistance of concept maps, low-achieving students could learn English with less pressure. The integration of concept maps and cooperative learning was recommended as a useful model to help low prior knowledge students catch up with their superior peers ( Zubaidah et al. , 2019 ). A recent study also showed the effectiveness of concept maps on the conceptual understanding of chemistry knowledge ( Turan-Oluk and Ekmekci, 2018 ). However, the results of studies concerning the effectiveness of concept maps are still inconsistent. While some studies indicated that using concept maps would help students understand subject contents significantly better ( Martínez et al. , 2013 ; Aguiar and Correia, 2016 ; Turan-Oluk and Ekmekci, 2018 ), several studies showed no significant difference when concept map teaching was compared with traditional teaching ( Markow and Lonning, 1998 ; Talbert et al. , 2020 ).

The purpose of this research is to investigate the effectiveness of using concept maps in teaching chemistry, thereby filling in the evidence gaps as mentioned. This study is driven by two research questions:

(1) What are the impacts of using concept maps as a learning tool on students’ performance?

In this study, the authors compared students' learning performance in traditional teaching (without concept maps) with their performance when using concept maps to investigate the impacts of concept mapping.

(2) What are students’ attitudes toward using concept maps as a learning tool?

The learning performance was examined through the topics of uncertainties of measurements (Topic 1) and acid–base chemistry (Topic 2). The first primary reason they were chosen was their importance to the participants of the study. The study was conducted in the General Chemistry course of the Department of Natural Resources and Environmental Studies (National Dong Hwa University, Taiwan). The undergraduate program in this department offers courses in both science and humanities strands. The topic of uncertainties of measurement in General Chemistry is the only topic that guides students in this department on how to calculate and report results of measurements. While the subject matter has importance for students studying environmental sciences and their future professional endeavors involving measures, it appears that the department's curriculum does not sufficiently reinforce this issue at advanced levels of education. This study prioritized the topic of acid–base because it is considered a core and fundamental topic to understand and predict diverse chemical phenomena. Multiple chemistry concepts relate to the acid–base topic, including chemical equilibrium, types of chemical reactions, and solutions. The second reason for choosing Topics 1 and 2 was that few studies on teaching these topics have been documented. For example, recent chemistry education research on the topic of uncertainties of measurements and acid–base has primarily focused on students’ misconceptions rather than teaching interventions.

Over the past 25 years, only a few studies on concept mapping in higher education chemistry courses have been conducted, and the findings concerning learning outcomes have been inconsistent ( Markow and Lonning, 1998 ; Su, 2013 ; Aguiar and Correia, 2016 ; Turan-Oluk and Ekmekci, 2018 ; Talbert et al. , 2020 ; Wang et al. , 2020 ; Wong et al. , 2020 ; Ye et al. , 2020 ). The present study is significant because it aims to fill the existing evidence gap regarding the effects of concept maps on learning chemistry, particularly focusing on the fill-in-the-nodes task. Additionally, the validated concept maps developed in this study could be used as a contribution to the contemporary theoretical frameworks developed by other science education researchers to develop multi-tier tests to diagnose students’ misconceptions. Moreover, in higher education, it is inevitable that foundation courses offered by interdisciplinary departments, which include both strands of science and strands of humanities, will have learners with low prior knowledge in chemistry. Along with contributions to extending knowledge of concept maps, the study aimed to use concept maps to help students with low prior knowledge in chemistry to learn the General Chemistry course more effectively. In the context of this study, the General Chemistry course is the only chemistry course that students have in their program.

Theoretical framework

Additionally, Ausubel assumed an individual's cognitive structure has a hierarchical organization. More general and inclusive concepts are in higher organization levels in the cognitive structure, and less inclusive concepts are subsumed under the general ones. With such an assumption, he proposed three mechanisms of learning. The first is derivative and correlative subsumption (when new concepts are at lower levels). The second one is superordinate learning (when new concepts are at higher levels). And the third one is combinatorial learning (when new concepts are at the same levels). Table 1 shows the definitions of three mechanisms of learning and their examples.

In practice, Ausubel proposed a teaching strategy called advance organizers. The function of these organizers is to bridge the gap between new learning knowledge and pre-existing knowledge. Learning materials are considered as advanced organisers if they are more abstract, general, and inclusive than the specific materials presented later and are relatable to students’ prior knowledge ( Ausubel, 2000 , p. 149). Since advance organizers consider what students have known, they can quickly reframe or build up their cognitive structure when interacting with the organizers. In this way, advance organizers serve as cognitive scaffoldings in learning.

Based on the Assimilation Theory of Ausubel, Novak developed concept maps as powerful advance organizers because concept maps mimic learners' cognitive structures which are assumed to have hierarchical structures. When students construct concept maps from scratch or fill in prepared concept maps, they will engage in meaningful learning ( Novak, 1998 , p. 71).

Literature review

What is a concept map.

Concept maps can be used as an assessment tool and a learning tool. Novak and colleagues originated the concept map from the need for a better assessment tool. The goal was to understand and probe the changes in students’ scientific knowledge, and the authors found it difficult to identify students’ understanding by examining interview transcripts ( Novak, 1990 ). According to the authors, one page of the concept map could represent 15–20 pages of the transcript without missing concept meanings expressed by interviewees ( Novak and Cañas, 2006b ). Novak used concept maps to ascertain what students know and changes in their knowledge over time. This particular use of concept maps was viewed as an assessment tool being applied to uncover students’ knowledge structure in chemistry education research ( Burrows and Mooring, 2015 ; Anzovino and Bretz, 2016 ).

Ruiz-Primo and co-workers (2001) categorized concept mapping tasks based on the degree of directedness, which depends on the number of components of concept maps provided. Fill-in-the-map is the task with the highest degree of directedness. In this task, the structure of a concept map, concepts, and linking phrases are provided, and map builders need to fill in missing concepts (fill-in-the-nodes) or linking phrases (fill-in-the-lines). If no components are provided, map builders will engage in a construct-a-map from scratch task with the lowest directedness degree.

Schau and colleagues (2001) reported three disadvantages of this kind of task, including time-consuming, lack of a universal scoring method, and effects of individual's communication skills. The degree of directedness of a concept map task can be increased by supplying more components. Concept maps with a high degree of directedness, like fill-in-the-lines or fill-in-the-nodes, can overcome the disadvantages. However, for the fill-in concept maps, the learning benefits of concept maps may not be optimized since students do not create structures of representations to generate their own understandings. In teaching practices, teachers assign types of concept map tasks to students according to their educational purposes and backgrounds of students.

Reasons for using concept maps as learning tools

Novak and Cañas (2006b) argued that concept maps could function as templates or scaffolds to help students organize and sequence new knowledge with prior knowledge. When students construct a concept map, they choose what concepts should be added and what relationships among concepts should be established to maintain the hierarchical structure and ensure the concept map is clean-looking. Accomplishing this task requires prior knowledge to engage with the meanings of concepts and their relationships. In consequence, the students promote meaningful learning.

Nesbit and Adesope wrote a comprehensive chapter about the theory and practice of concept maps (2013). They summarized the main reasons posed by theorists. According to the chapter, concept maps can reduce learners’ cognitive load. First, reading concept maps enables learners to share loads of verbal processing with visual processing. The reason is the connections of concepts create meaningful syntactic units that contain both verbal and visual information. Second, transferring texts into concept maps can integrate a concept with multiple occurrences into a node. In this way, concept maps can show the macrostructure and relationships among concepts. Consequently, learners can reduce the visual search process and relate ideas of the texts more efficiently.

Given that concept maps seem to facilitate learning successfully, they do have disadvantages. First, it is time-consuming to create a good quality concept map and train students to master concept mapping skills. Jang (2010) examined how students ( n = 114) thought about concept maps. The students said concept mapping was time-consuming and challenging to write. An overview report by Lawless and colleagues (1998) claimed that it took time to train students to master concept mapping skills. Hence, concept maps may not be an ideal learning tool for a course with a tight schedule. Second, compared with reading text from a page, reading concept maps may need extraneous cognitive load because readers have to decide where to start ( Nesbit and Adesope, 2013 ). Blankenship and Dansereau (2000) referred to the hesitation of reading maps as map shock.

Studies on using concept maps in chemistry classrooms

Schwendimann (2019) conducted a meta-analysis on the concept map learning of science courses, including science teachers and schools at all levels, and found that a concept map was a universal tool for teaching, learning, and assessment purposes. A concept map was also a powerful tool that can support the integration of scientific knowledge and understanding of the context of complex concepts. However, the concept map has not been widely used as other learning and evaluation tools. It suggested that more science teachers devote themselves to concept map design, implement concept map teaching, and assist students in learning concepts.

Additionally, in the systematic review of Machado and Carvalho (2020) on 60 university courses (medicine, education, business, engineering, and science) from 1988 to 2018, they found that the concept map can help college students develop critical thinking, problem-solving and in-depth understanding of concepts. Implementing concept map teaching is challenging because students struggle with choosing concepts and connectives, resist the mentality of using concept maps, and find it difficult to use concept mapping software. However, through timely and appropriate guidance by teachers, students can finally acknowledge that concept maps are beneficial to meaningful learning.

Doing a meta-analysis goes beyond this study's scope. Alternatively, the authors reviewed studies that targeted chemistry classrooms in higher education. Each of the following research was discussed in turn. The results of the studies were discrepant from the effects of concept maps on students’ learning performance.

On the one hand, concept maps could show no effects on students’ learning ( Markow and Lonning, 1998 ; Talbert et al. , 2020 ; Ye et al. , 2020 ). Markow and co-workers (1998) conducted quasi-experiment research on 32 non-science majors enrolled in Principles of Inorganic and Organic Chemistry. The treatment group needed to construct pre-lab and post-lab concept maps, whereas the control group wrote essays to explain experiments. In the research, a 25-item test was used as a pre-test and post-test to measure students’ understanding. The result showed no significant difference between the treatment group and control group regarding students’ conceptual understanding. However, since the authors analyzed pre-test and post-test separately, the result inflated type 1 error and did not consider the effects of the pre-test on the post-test. In 2020, Talbert and colleagues reproduced the same research design on 238 students in the General Chemistry course ( Talbert et al. , 2020 ). Students in the treatment group constructed concept maps of chapters and connected important concepts of different chapters. Students in the control group wrote a weekly journal to summarize what they learned. Concept inventory was adopted to serve as a pre-test and post-test. The authors used multiple regression to hold constant the effects of the pre-test on the post-test, and the result indicated that both groups had no significant difference in the post-test. Compared with the study of Markow and Lonning, Talbert concluded with a more robust statistical technique. However, in the latter study, the treatment and control groups were taught by two different instructors, which led the instructors to become independent variables. Consistent with the findings of Markow and Talbert, the research conducted on 111 students in General Chemistry by Ye et al. (2020) also indicated learning with concept maps brought no significant difference when compared with the control group. The study of Ye also had different teaching assistants for the control group and the treatment group.

On the other hand, several studies showed positive impacts of concept maps on students’ conceptual understanding of chemistry. A quasi-experiment study by Su (2013) compared the learning achievements of students ( n = 75) with and without concept map guidance on the topic of molecular chemistry. The analysis of covariance concluded that students in the treatment group significantly outperformed. Rather than comparing control and treatment groups, some research focused on the effectiveness of different concept mapping techniques. Table 2 summarizes the results of these studies.

From the literature review, scarce evidence reported concept maps’ benefits in chemistry classrooms in higher education. With restrictions to peer-reviewed journals, the authors found only five studies. Among the studies, only Su's research indicated positive effects of concept maps based on a quasi-experimental control group design ( Su, 2013 ).

Students’ attitudes toward concept mapping

Student's prior knowledge and concept mapping techniques.

Concept map tasks vary from low directedness to high directness, and research showed that the latter type is more likely to guide students with low prior knowledge to favorable learning outcomes ( Chang et al. , 2001 ; Wang and Dwyer, 2004 ). The study of Chang had 48 participants ( Chang et al. , 2001 ). The authors used three types of concept map tasks in biology class: construct-by-self (concepts provided), construct-on-scaffold (concepts and structure provided), and paper-and-pencil. Although students in the construct-on-scaffold group had the lowest prior knowledge, their performance after the intervention was the highest. Wang and Dwyer (2004) compared the effects of low and high directedness concept maps on students’ achievements. The study had 290 participants, and the result indicated low prior-knowledge students learned better with high directedness concept map tasks. With such evidence of the benefits of high directedness concept maps for low prior knowledge students, the authors of this study decided to use fill-in-the-nodes concept mapping tasks for the General Chemistry course.

Research method

Research design.

Students in the treatment group received training on concept mapping. The training took 30 minutes in the second week of the course. They learned the definition of a concept map and how to construct a concept map appropriately. In training, the students practiced creating a concept map with provided concepts. The focus question was “What are the functions of a tree?”. The lecturer and the teaching assistant (TA) of the course went around the classroom and gave students feedback about their work. At the end of the training, the lecturer explained the fill-in-the-nodes task to the students.

After concept map training, the students received the pre-test and then learned Topic 1 and Topic 2 from lectures in class. After that, they were assigned concept maps with missing nodes as exercises. The students needed to complete the exercises and submit their answers to the TA. The TA gave them feedback about their concept maps. When students had questions or misunderstandings about the exercises, the lecturer of the course and the TA guided them without providing answers. Before the post-test one week, the lecturer summarized the topics based on validated concept maps. The lecturer then gave answers and explained more about connections in the maps.

After learning Topic 1 and Topic 2, the students in the treatment group filled in a questionnaire to express their attitudes toward the tools.

Both treatment and control groups received instructions from the same lecturer and the same teaching time for Topic 1 (3 hours) and Topic 2 (12 hours). While the control groups did exercises in the textbook, the treatment group engaged in concept map exercises. At the end of the topics, both groups had exercise discussions based on the keys of the exercises with the lecturer. In the case of the treatment group, the exercises in the textbook were introduced as optional practices to maximize the utility of the textbook.

Research participants

Concept maps (learning tools) and concept tests.

Table 5 and Fig. 3 show a sample of the propositions and the concept map of the focused question: What calculation rules are associated with significant figures?

The concept tests in this research are achievement tests, which attempt to measure “an individual's knowledge or skill in a given area or subject” ( Fraenkel et al. , 2011 , 127). The propositional knowledge statements of the two topics serve as content domains for developing the tests. The items of the tests were written by the authors and then later served as the pre-test and the post-test in this study. The alignment between the propositions and the items of the test was judged by the reviewers to assure the face validity. Most of the chemical names, numbers, and examples in the post-test have been changed in the pre-tests to reduce the memorization of items. Fig. 4 illustrates the process of developing concept maps and concept tests. The concept tests consist of twenty-six items for Topic 1 (total score = 26) and fourteen items for Topic 2 (total score = 47). The concept tests had true-false items and multiple-choice items with a single answer or multiple answers (see the Appendix, ESI † ). The reliabilities of the concept tests were evaluated by the values of Cronbach alpha – an internal consistency coefficient. The concept test of Topic 1 obtained a Cronbach alpha of 0.72, indicating a moderate level of reliability. The concept test of Topic 2 had low reliability since the Cronbach alpha was 0.63. One possible reason was the limited number of items. Moreover, concept tests tend to measure students’ understanding of several concepts of a topic, so it Is understandable for concept tests to have a low Conbrach alpha ( Adams and Wieman, 2011 ; Berger and Hänze, 2015 ). Pearson correlation analyses between concept tests and exam scores of the topics were performed to check the predictive validity of the concept tests. The results showed that the predictive validity was confirmed for both Topic 1 ( r = 0.36, p < 0.05) and Topic 2 ( r = 0.517, p < 0.05).

Attitudinal questionnaire

Data analysis.

To answer the research question 2, descriptive statistics (means and standard deviations) were calculated for the three components of the questionnaire. Besides, the authors grouped and summed the number of responses on “highly agree” and “agree” as “agree” for each item. Similarly, “highly disagree” and “disagree” were grouped and summed as “disagree”. The percentages of responses were also reported to examine students’ attitudes toward concept maps.

Impacts of concept maps on students’ learning

For Topic 2, the mean (SD) of the pre-test and post-test of the treatment group were 30.20 (6.50) and 35.33 (5.47) respectively, and those of the control group were 28.17 (4.31) and 30.54 (5.66) respectively. Since the data of Topic 2 did not meet the assumption of homogeneity of the regression slope, the authors used the Johnson–Neyman procedure to examine the difference in the post-test of two groups with restriction to a certain range of pre-test. Fig. 5 is the Johnson–Neyman plot retrieved from the Excel workbook. In the plot, the vertical axis shows the simple slope of the group predicting the post-test, and the horizontal axis shows the pre-test values. The shaded region indicates 95% confidence intervals, and any values of the pre-test for which the shaded regions contain zero have an insignificant effect of the group on the post-test. It was clear that the significant range is on the left-hand side of 30.7. By examining the post-test values of the corresponding pre-test values, which are less than 30.7 in Fig. 6 (the scatterplot of the pre-test and the post-test), it could be concluded that the post-test of the treatment group was significantly higher than that of the control group. The d effect size of the treatment group was large ( d = 0.86) and was also higher than that of the control group ( d = 0.48).

Attitude toward concept mapping

Fig. 7 shows means and percentages of responses to items of cognition-acknowledging the usefulness of concept maps. Inspection of the items revealed that the treatment group agreed that concept maps were useful. The percentage of the agreement ranged from 58% to 77%. However, more students had neutral opinions about item 6 – “Concept maps improve my thought system”, item 8 – “Concept map lets me learn a topic permanently”, and item 13 – “Concept Map is useful for sharing my knowledge of the topic with others”.

Regarding the items related to the feeling about using concept maps, only item 18 – “When I create Concept maps, I participate more actively in lessons” received the agreement of most of the students, 52%. Most of the students chose neutral options for the other items, ranging from 52% to 61%, as shown in Fig. 8 .

Concerning the items related to the intention to use concept maps as a learning tool, most students disagreed with negative items, which means they intended to use this tool in learning. The percentage of disagreement ranged from 42% to 65% as shown in Fig. 9 . The items that received more neutral opinions were item 3 – “Preparing Concept maps is wasting my time.”, item 7 – “It's hard to work with Concept maps”, item 15 – “I like to learn about the Concept map”, item 19 – “I prefer studying for the topic using other ways than preparing Concept maps”. It was clear from these four items that the students still had a certain degree of hesitation to learn and use concept maps.

Discussion and conclusion

1. Concept maps could function as templates or scaffolds to help students organize and sequence new knowledge with prior knowledge ( Eppler, 2006 ).

2. Reading concept maps could reduce cognitive load ( Nesbit and Adesope, 2013 ).

3. Concept maps could provide a holistic view of contents ( Turan-Oluk and Ekmekci, 2018 ).

Through the quasi-experimental control group design, this study has given a new insight into the positive effect of fill-in-the-nodes concept maps on the learning chemistry of low prior knowledge students. If only restricting to the quasi-experimental control group design, the results match the study of Su (2013) that reported using concept maps in teaching chemistry had some advantages over traditional teaching. However, the study results are inconsistent with those of Markow and Lonning, Talbert, Ye ( Markow and Lonning, 1998 ; Talbert et al. , 2020 ; Ye et al. , 2020 ). These studies showed no significant difference between treatment and control groups. The nature of teaching contents and research design could be the reasons for the inconsistency in the findings. While this present study focused on the lecturing course-General Chemistry, Markow and Lonning researched chemistry laboratory courses. Talbert and Ye employed different teaching staff which could be a confounding variable in the research. However, only one lecturer taught in both the control and treatment groups in the present study.

Generally, the treatment group students acknowledge the usefulness of concept maps and have the intention to use concept maps as a learning tool, but interestingly they neither have a positive nor negative feeling about concept maps. The findings of this study show that the students recognize the usefulness of concept maps, which are similar to the findings of Markow and Lonning, and Turan-Oluk. Despite this, the students still have hesitation in using concept maps in their learning. Possible reasons for this result could be:

1. The unfamiliarity with the concept mapping made students frustrated ( Chiou, 2008 ).

2. Doing concept maps was time-consuming and took extra work ( Brondfield et al. , 2019 ).

3. Students already had preferred learning methods ( Brondfield et al. , 2019 ).

Further research like focus group interviews needs to be conducted to have more in-depth insight into why students are unwilling to use concept maps.

In conclusion, fill-in-the-nodes concept mapping indeed is a helpful learning tool for students with low prior knowledge. Concept maps promote students’ understanding of Topic 1 (Uncertainties of measurements) and Topic 2 (Acid–base). Compared with the control group, students learning with concept maps have significantly higher achievements. Moreover, students have moderate positive attitudes toward this tool. They believe concept maps are a useful learning tool that can help them understand key concepts.

Practical implications, limitations, and future studies

For practical implications in the classroom, the authors suggest chemistry instructors consider consulting the following sequence:

1. Decide what type of concept mapping task is appropriate for students. If the students are new to concept maps, fill-in-the-nodes task is a good start, especially for low prior knowledge students.

2. Identify key propositions of topics from reading materials, such as textbooks, websites, and syllabi.

3. Develop standard concept maps and concept tests based on key propositions. The standard concept maps should have hierarchical structures and focus questions to ensure their intelligibility.

4. Give concept maps training to students. The training should allocate sufficient time (at least 30 minutes) to cover the definition of concept maps, features, functions of concept maps, examples, and practices. As indicated in this study, students have hesitation in using concept maps, so instructors may consider sharing the benefits of concept maps through empirical studies to engage students in this learning tool.

5. Implement lectures and give concept map exercises to students.

6. Summarize the topic based on standard concept maps. The students get correct answers to concept maps exercises from this step.

Given that the results of the present study are promising for the effectiveness of concept mapping, it has several important limitations which need to be considered. Firstly, this study is a classroom-based study which involved convenience sampling and small number of participants. Therefore, the generalizability of the findings is limited. Future research should focus on developing concept maps for other topics and investigating the learning impacts of these concept maps on classes with larger sizes. This kind of study will bring tremendous practical benefits to the chemistry education community. Secondly, the intervention in this study seems to lack elements of learning engagement, leading to the students’ hesitation in concept mapping. For this reason, future research could consider studying what makes students reluctant to use concept maps for learning, as well as exploring strategies to enhance students’ engagement with concept mapping. For the first question, it is necessary to have in-depth interviews with students throughout concept mapping interventions. For the second question, utilizing interactive online platforms which enable teachers to provide immediate feedback on students' concept maps could be a promising approach. The free Web-based inquiry science environment developed by UC Berkeley might be used for this purpose because it offers concept mapping exercises in its authoring tools.

Conflicts of interest

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