synthesis of the literature

• University of Oregon Libraries
• Research Guides

How to Write a Literature Review

• 6. Synthesize
• Literature Reviews: A Recap
• Reading Journal Articles
• Does it Describe a Literature Review?
• 1. Identify the Question
• 2. Review Discipline Styles
• Searching Article Databases
• Finding Full-Text of an Article
• Citation Chaining
• When to Stop Searching
• 4. Manage Your References
• 5. Critically Analyze and Evaluate

Synthesis Visualization

Synthesis matrix example.

• 7. Write a Literature Review

• Synthesis Worksheet

About Synthesis

Approaches to synthesis.

You can sort the literature in various ways, for example:

How to Begin?

Read your sources carefully and find the main idea(s) of each source

Look for similarities in your sources – which sources are talking about the same main ideas? (for example, sources that discuss the historical background on your topic)

Use the worksheet (above) or synthesis matrix (below) to get organized

This work can be messy. Don't worry if you have to go through a few iterations of the worksheet or matrix as you work on your lit review!

Four Examples of Student Writing

In the four examples below, only ONE shows a good example of synthesis: the fourth column, or  Student D . For a web accessible version, click the link below the image.

Long description of "Four Examples of Student Writing" for web accessibility

• Download a copy of the "Four Examples of Student Writing" chart

Click on the example to view the pdf.

From Jennifer Lim

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• Last Updated: May 1, 2024 3:30 PM
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• Write a Literature Review
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Get Organized

• Lit Review Prep Use this template to help you evaluate your sources, create article summaries for an annotated bibliography, and a synthesis matrix for your lit review outline.

Synthesize your Information

Synthesize: combine separate elements to form a whole.

Synthesis Matrix

A synthesis matrix helps you record the main points of each source and document how sources relate to each other.

After summarizing and evaluating your sources, arrange them in a matrix or use a citation manager to help you see how they relate to each other and apply to each of your themes or variables.  

By arranging your sources by theme or variable, you can see how your sources relate to each other, and can start thinking about how you weave them together to create a narrative.

• Step-by-Step Approach
• Example Matrix from NSCU
• Matrix Template
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• Last Updated: Sep 26, 2023 10:25 AM
• URL: https://guides.library.jhu.edu/lit-review

Literature Syntheis 101

How To Synthesise The Existing Research (With Examples)

By: Derek Jansen (MBA) | Expert Reviewer: Eunice Rautenbach (DTech) | August 2023

One of the most common mistakes that students make when writing a literature review is that they err on the side of describing the existing literature rather than providing a critical synthesis of it. In this post, we’ll unpack what exactly synthesis means and show you how to craft a strong literature synthesis using practical examples.

This post is based on our popular online course, Literature Review Bootcamp . In the course, we walk you through the full process of developing a literature review, step by step. If it’s your first time writing a literature review, you definitely want to use this link to get 50% off the course (limited-time offer).

Overview: Literature Synthesis

• What exactly does “synthesis” mean?
• Aspect 1: Agreement
• Aspect 2: Disagreement
• Aspect 3: Key theories
• Aspect 4: Contexts
• Aspect 5: Methodologies
• Bringing it all together

What does “synthesis” actually mean?

As a starting point, let’s quickly define what exactly we mean when we use the term “synthesis” within the context of a literature review.

Simply put, literature synthesis means going beyond just describing what everyone has said and found. Instead, synthesis is about bringing together all the information from various sources to present a cohesive assessment of the current state of knowledge in relation to your study’s research aims and questions .

Put another way, a good synthesis tells the reader exactly where the current research is “at” in terms of the topic you’re interested in – specifically, what’s known , what’s not , and where there’s a need for more research .

So, how do you go about doing this?

Well, there’s no “one right way” when it comes to literature synthesis, but we’ve found that it’s particularly useful to ask yourself five key questions when you’re working on your literature review. Having done so,  you can then address them more articulately within your actual write up. So, let’s take a look at each of these questions.

1. Points Of Agreement

The first question that you need to ask yourself is: “Overall, what things seem to be agreed upon by the vast majority of the literature?”

For example, if your research aim is to identify which factors contribute toward job satisfaction, you’ll need to identify which factors are broadly agreed upon and “settled” within the literature. Naturally, there may at times be some lone contrarian that has a radical viewpoint , but, provided that the vast majority of researchers are in agreement, you can put these random outliers to the side. That is, of course, unless your research aims to explore a contrarian viewpoint and there’s a clear justification for doing so. 

Identifying what’s broadly agreed upon is an essential starting point for synthesising the literature, because you generally don’t want (or need) to reinvent the wheel or run down a road investigating something that is already well established . So, addressing this question first lays a foundation of “settled” knowledge.

Need a helping hand?

2. Points Of Disagreement

Related to the previous point, but on the other end of the spectrum, is the equally important question: “Where do the disagreements lie?” .

In other words, which things are not well agreed upon by current researchers? It’s important to clarify here that by disagreement, we don’t mean that researchers are (necessarily) fighting over it – just that there are relatively mixed findings within the empirical research , with no firm consensus amongst researchers.

This is a really important question to address as these “disagreements” will often set the stage for the research gap(s). In other words, they provide clues regarding potential opportunities for further research, which your study can then (hopefully) contribute toward filling. If you’re not familiar with the concept of a research gap, be sure to check out our explainer video covering exactly that .

3. Key Theories

The next question you need to ask yourself is: “Which key theories seem to be coming up repeatedly?” .

Within most research spaces, you’ll find that you keep running into a handful of key theories that are referred to over and over again. Apart from identifying these theories, you’ll also need to think about how they’re connected to each other. Specifically, you need to ask yourself:

• Are they all covering the same ground or do they have different focal points  or underlying assumptions ?
• Do some of them feed into each other and if so, is there an opportunity to integrate them into a more cohesive theory?
• Do some of them pull in different directions ? If so, why might this be?
• Do all of the theories define the key concepts and variables in the same way, or is there some disconnect? If so, what’s the impact of this ?

Simply put, you’ll need to pay careful attention to the key theories in your research area, as they will need to feature within your theoretical framework , which will form a critical component within your final literature review. This will set the foundation for your entire study, so it’s essential that you be critical in this area of your literature synthesis.

If this sounds a bit fluffy, don’t worry. We deep dive into the theoretical framework (as well as the conceptual framework) and look at practical examples in Literature Review Bootcamp . If you’d like to learn more, take advantage of our limited-time offer to get 60% off the standard price.

4. Contexts

The next question that you need to address in your literature synthesis is an important one, and that is: “Which contexts have (and have not) been covered by the existing research?” .

For example, sticking with our earlier hypothetical topic (factors that impact job satisfaction), you may find that most of the research has focused on white-collar , management-level staff within a primarily Western context, but little has been done on blue-collar workers in an Eastern context. Given the significant socio-cultural differences between these two groups, this is an important observation, as it could present a contextual research gap .

In practical terms, this means that you’ll need to carefully assess the context of each piece of literature that you’re engaging with, especially the empirical research (i.e., studies that have collected and analysed real-world data). Ideally, you should keep notes regarding the context of each study in some sort of catalogue or sheet, so that you can easily make sense of this before you start the writing phase. If you’d like, our free literature catalogue worksheet is a great tool for this task.

5. Methodological Approaches

Last but certainly not least, you need to ask yourself the question: “What types of research methodologies have (and haven’t) been used?”

For example, you might find that most studies have approached the topic using qualitative methods such as interviews and thematic analysis. Alternatively, you might find that most studies have used quantitative methods such as online surveys and statistical analysis.

But why does this matter?

Well, it can run in one of two potential directions . If you find that the vast majority of studies use a specific methodological approach, this could provide you with a firm foundation on which to base your own study’s methodology . In other words, you can use the methodologies of similar studies to inform (and justify) your own study’s research design .

On the other hand, you might argue that the lack of diverse methodological approaches presents a research gap , and therefore your study could contribute toward filling that gap by taking a different approach. For example, taking a qualitative approach to a research area that is typically approached quantitatively. Of course, if you’re going to go against the methodological grain, you’ll need to provide a strong justification for why your proposed approach makes sense. Nevertheless, it is something worth at least considering.

Regardless of which route you opt for, you need to pay careful attention to the methodologies used in the relevant studies and provide at least some discussion about this in your write-up. Again, it’s useful to keep track of this on some sort of spreadsheet or catalogue as you digest each article, so consider grabbing a copy of our free literature catalogue if you don’t have anything in place.

Bringing It All Together

Alright, so we’ve looked at five important questions that you need to ask (and answer) to help you develop a strong synthesis within your literature review.  To recap, these are:

• Which things are broadly agreed upon within the current research?
• Which things are the subject of disagreement (or at least, present mixed findings)?
• Which theories seem to be central to your research topic and how do they relate or compare to each other?
• Which contexts have (and haven’t) been covered?
• Which methodological approaches are most common?

Importantly, you’re not just asking yourself these questions for the sake of asking them – they’re not just a reflection exercise. You need to weave your answers to them into your actual literature review when you write it up. How exactly you do this will vary from project to project depending on the structure you opt for, but you’ll still need to address them within your literature review, whichever route you go.

The best approach is to spend some time actually writing out your answers to these questions, as opposed to just thinking about them in your head. Putting your thoughts onto paper really helps you flesh out your thinking . As you do this, don’t just write down the answers – instead, think about what they mean in terms of the research gap you’ll present , as well as the methodological approach you’ll take . Your literature synthesis needs to lay the groundwork for these two things, so it’s essential that you link all of it together in your mind, and of course, on paper.

Psst… there’s more!

This post is an extract from our bestselling short course, Literature Review Bootcamp . If you want to work smart, you don't want to miss this .

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Literature Review Basics

• What is a Literature Review?
• Synthesizing Research
• Using Research & Synthesis Tables
• Additional Resources

Synthesis: What is it?

First, let's be perfectly clear about what synthesizing your research isn't :

• - It isn't  just summarizing the material you read
• - It isn't  generating a collection of annotations or comments (like an annotated bibliography)
• - It isn't  compiling a report on every single thing ever written in relation to your topic

When you  synthesize  your research, your job is to help your reader understand the current state of the conversation on your topic, relative to your research question.  That may include doing the following:

• - Selecting and using representative work on the topic
• - Identifying and discussing trends in published data or results
• - Identifying and explaining the impact of common features (study populations, interventions, etc.) that appear frequently in the literature
• - Explaining controversies, disputes, or central issues in the literature that are relevant to your research question
• - Identifying gaps in the literature, where more research is needed
• - Establishing the discussion to which your own research contributes and demonstrating the value of your contribution

Essentially, you're telling your reader where they are (and where you are) in the scholarly conversation about your project.

Synthesis: How do I do it?

Synthesis, step by step.

This is what you need to do  before  you write your review.

• Identify and clearly describe your research question (you may find the Formulating PICOT Questions table at  the Additional Resources tab helpful).
• Collect sources relevant to your research question.
• Organize and describe the sources you've found -- your job is to identify what  types  of sources you've collected (reviews, clinical trials, etc.), identify their  purpose  (what are they measuring, testing, or trying to discover?), determine the  level of evidence  they represent (see the Levels of Evidence table at the Additional Resources tab ), and briefly explain their  major findings . Use a Research Table to document this step.
• Study the information you've put in your Research Table and examine your collected sources, looking for  similarities  and  differences . Pay particular attention to  populations ,   methods  (especially relative to levels of evidence), and  findings .
• Analyze what you learn in (4) using a tool like a Synthesis Table. Your goal is to identify relevant themes, trends, gaps, and issues in the research.  Your literature review will collect the results of this analysis and explain them in relation to your research question.

Analysis tips

• - Sometimes, what you  don't  find in the literature is as important as what you do find -- look for questions that the existing research hasn't answered yet.
• - If any of the sources you've collected refer to or respond to each other, keep an eye on how they're related -- it may provide a clue as to whether or not study results have been successfully replicated.
• - Sorting your collected sources by level of evidence can provide valuable insight into how a particular topic has been covered, and it may help you to identify gaps worth addressing in your own work.
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How to Synthesize Written Information from Multiple Sources

Shona McCombes

Content Manager

B.A., English Literature, University of Glasgow

Shona McCombes is the content manager at Scribbr, Netherlands.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

When you write a literature review or essay, you have to go beyond just summarizing the articles you’ve read – you need to synthesize the literature to show how it all fits together (and how your own research fits in).

Synthesizing simply means combining. Instead of summarizing the main points of each source in turn, you put together the ideas and findings of multiple sources in order to make an overall point.

At the most basic level, this involves looking for similarities and differences between your sources. Your synthesis should show the reader where the sources overlap and where they diverge.

Unsynthesized Example

Franz (2008) studied undergraduate online students. He looked at 17 females and 18 males and found that none of them liked APA. According to Franz, the evidence suggested that all students are reluctant to learn citations style. Perez (2010) also studies undergraduate students. She looked at 42 females and 50 males and found that males were significantly more inclined to use citation software ( p < .05). Findings suggest that females might graduate sooner. Goldstein (2012) looked at British undergraduates. Among a sample of 50, all females, all confident in their abilities to cite and were eager to write their dissertations.

Synthesized Example

Studies of undergraduate students reveal conflicting conclusions regarding relationships between advanced scholarly study and citation efficacy. Although Franz (2008) found that no participants enjoyed learning citation style, Goldstein (2012) determined in a larger study that all participants watched felt comfortable citing sources, suggesting that variables among participant and control group populations must be examined more closely. Although Perez (2010) expanded on Franz’s original study with a larger, more diverse sample…

Step 1: Organize your sources

After collecting the relevant literature, you’ve got a lot of information to work through, and no clear idea of how it all fits together.

Before you can start writing, you need to organize your notes in a way that allows you to see the relationships between sources.

One way to begin synthesizing the literature is to put your notes into a table. Depending on your topic and the type of literature you’re dealing with, there are a couple of different ways you can organize this.

Summary table

A summary table collates the key points of each source under consistent headings. This is a good approach if your sources tend to have a similar structure – for instance, if they’re all empirical papers.

Each row in the table lists one source, and each column identifies a specific part of the source. You can decide which headings to include based on what’s most relevant to the literature you’re dealing with.

For example, you might include columns for things like aims, methods, variables, population, sample size, and conclusion.

For each study, you briefly summarize each of these aspects. You can also include columns for your own evaluation and analysis.

The summary table gives you a quick overview of the key points of each source. This allows you to group sources by relevant similarities, as well as noticing important differences or contradictions in their findings.

Synthesis matrix

A synthesis matrix is useful when your sources are more varied in their purpose and structure – for example, when you’re dealing with books and essays making various different arguments about a topic.

Each column in the table lists one source. Each row is labeled with a specific concept, topic or theme that recurs across all or most of the sources.

Then, for each source, you summarize the main points or arguments related to the theme.

The purposes of the table is to identify the common points that connect the sources, as well as identifying points where they diverge or disagree.

Step 2: Outline your structure

Now you should have a clear overview of the main connections and differences between the sources you’ve read. Next, you need to decide how you’ll group them together and the order in which you’ll discuss them.

For shorter papers, your outline can just identify the focus of each paragraph; for longer papers, you might want to divide it into sections with headings.

There are a few different approaches you can take to help you structure your synthesis.

If your sources cover a broad time period, and you found patterns in how researchers approached the topic over time, you can organize your discussion chronologically .

That doesn’t mean you just summarize each paper in chronological order; instead, you should group articles into time periods and identify what they have in common, as well as signalling important turning points or developments in the literature.

If the literature covers various different topics, you can organize it thematically .

That means that each paragraph or section focuses on a specific theme and explains how that theme is approached in the literature.

Source Used with Permission: The Chicago School

If you’re drawing on literature from various different fields or they use a wide variety of research methods, you can organize your sources methodologically .

That means grouping together studies based on the type of research they did and discussing the findings that emerged from each method.

If your topic involves a debate between different schools of thought, you can organize it theoretically .

That means comparing the different theories that have been developed and grouping together papers based on the position or perspective they take on the topic, as well as evaluating which arguments are most convincing.

Step 3: Write paragraphs with topic sentences

What sets a synthesis apart from a summary is that it combines various sources. The easiest way to think about this is that each paragraph should discuss a few different sources, and you should be able to condense the overall point of the paragraph into one sentence.

This is called a topic sentence , and it usually appears at the start of the paragraph. The topic sentence signals what the whole paragraph is about; every sentence in the paragraph should be clearly related to it.

A topic sentence can be a simple summary of the paragraph’s content:

“Early research on [x] focused heavily on [y].”

For an effective synthesis, you can use topic sentences to link back to the previous paragraph, highlighting a point of debate or critique:

“Several scholars have pointed out the flaws in this approach.” “While recent research has attempted to address the problem, many of these studies have methodological flaws that limit their validity.”

By using topic sentences, you can ensure that your paragraphs are coherent and clearly show the connections between the articles you are discussing.

As you write your paragraphs, avoid quoting directly from sources: use your own words to explain the commonalities and differences that you found in the literature.

Don’t try to cover every single point from every single source – the key to synthesizing is to extract the most important and relevant information and combine it to give your reader an overall picture of the state of knowledge on your topic.

Step 4: Revise, edit and proofread

Like any other piece of academic writing, synthesizing literature doesn’t happen all in one go – it involves redrafting, revising, editing and proofreading your work.

Checklist for Synthesis

•   Do I introduce the paragraph with a clear, focused topic sentence?
•   Do I discuss more than one source in the paragraph?
•   Do I mention only the most relevant findings, rather than describing every part of the studies?
•   Do I discuss the similarities or differences between the sources, rather than summarizing each source in turn?
•   Do I put the findings or arguments of the sources in my own words?
•   Is the paragraph organized around a single idea?
•   Is the paragraph directly relevant to my research question or topic?
•   Is there a logical transition from this paragraph to the next one?

Further Information

How to Synthesise: a Step-by-Step Approach

Help…I”ve Been Asked to Synthesize!

Learn how to Synthesise (combine information from sources)

How to write a Psychology Essay

Library Guides

Literature reviews: synthesis.

• Criticality

Synthesise Information

So, how can you create paragraphs within your literature review that demonstrates your knowledge of the scholarship that has been done in your field of study?  

You will need to present a synthesis of the texts you read.  

Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains synthesis for us in the following video:  

Synthesising Texts  

What is synthesis? 

Synthesis is an important element of academic writing, demonstrating comprehension, analysis, evaluation and original creation.  

With synthesis you extract content from different sources to create an original text. While paraphrase and summary maintain the structure of the given source(s), with synthesis you create a new structure.  

The sources will provide different perspectives and evidence on a topic. They will be put together when agreeing, contrasted when disagreeing. The sources must be referenced.  

Perfect your synthesis by showing the flow of your reasoning, expressing critical evaluation of the sources and drawing conclusions.  

When you synthesise think of "using strategic thinking to resolve a problem requiring the integration of diverse pieces of information around a structuring theme" (Mateos and Sole 2009, p448). 

Synthesis is a complex activity, which requires a high degree of comprehension and active engagement with the subject. As you progress in higher education, so increase the expectations on your abilities to synthesise. 

How to synthesise in a literature review: 

Identify themes/issues you'd like to discuss in the literature review. Think of an outline.  

Read the literature and identify these themes/issues.  

Critically analyse the texts asking: how does the text I'm reading relate to the other texts I've read on the same topic? Is it in agreement? Does it differ in its perspective? Is it stronger or weaker? How does it differ (could be scope, methods, year of publication etc.). Draw your conclusions on the state of the literature on the topic.  

Start writing your literature review, structuring it according to the outline you planned.  

Put together sources stating the same point; contrast sources presenting counter-arguments or different points.  

Present your critical analysis.  

Always provide the references. 

The best synthesis requires a "recursive process" whereby you read the source texts, identify relevant parts, take notes, produce drafts, re-read the source texts, revise your text, re-write... (Mateos and Sole, 2009). 

What is good synthesis?  

The quality of your synthesis can be assessed considering the following (Mateos and Sole, 2009, p439):  

Integration and connection of the information from the source texts around a structuring theme. 

Selection of ideas necessary for producing the synthesis. 

Appropriateness of the interpretation.  

Elaboration of the content.  

Example of Synthesis

Original texts (fictitious): 

Synthesis: 

Animal experimentation is a subject of heated debate. Some argue that painful experiments should be banned. Indeed it has been demonstrated that such experiments make animals suffer physically and psychologically (Chowdhury 2012; Panatta and Hudson 2016). On the other hand, it has been argued that animal experimentation can save human lives and reduce harm on humans (Smith 2008). This argument is only valid for toxicological testing, not for tests that, for example, merely improve the efficacy of a cosmetic (Turner 2015). It can be suggested that animal experimentation should be regulated to only allow toxicological risk assessment, and the suffering to the animals should be minimised.   

Bibliography

Mateos, M. and Sole, I. (2009). Synthesising Information from various texts: A Study of Procedures and Products at Different Educational Levels. European Journal of Psychology of Education,  24 (4), 435-451. Available from https://doi.org/10.1007/BF03178760 [Accessed 29 June 2021].

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• Last Updated: Nov 18, 2023 10:56 PM
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Literature Review How To

• Things To Consider
• Synthesizing Sources
• Video Tutorials
• Books On Literature Reviews

What is Synthesis

What is Synthesis? Synthesis writing is a form of analysis related to comparison and contrast, classification and division. On a basic level, synthesis requires the writer to pull together two or more summaries, looking for themes in each text. In synthesis, you search for the links between various materials in order to make your point. Most advanced academic writing, including literature reviews, relies heavily on synthesis. (Temple University Writing Center)  

How To Synthesize Sources in a Literature Review

Literature reviews synthesize large amounts of information and present it in a coherent, organized fashion. In a literature review you will be combining material from several texts to create a new text – your literature review.

You will use common points among the sources you have gathered to help you synthesize the material. This will help ensure that your literature review is organized by subtopic, not by source. This means various authors' names can appear and reappear throughout the literature review, and each paragraph will mention several different authors. 

When you shift from writing summaries of the content of a source to synthesizing content from sources, there is a number things you must keep in mind: 

• Look for specific connections and or links between your sources and how those relate to your thesis or question.
• When writing and organizing your literature review be aware that your readers need to understand how and why the information from the different sources overlap.
• Organize your literature review by the themes you find within your sources or themes you have identified. 
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Literature Reviews

• 5. Synthesize your findings
• Getting started
• Types of reviews
• 1. Define your research question
• 2. Plan your search
• 3. Search the literature
• 4. Organize your results

How to synthesize

Approaches to synthesis.

• 6. Write the review
• Artificial intelligence (AI) tools
• Thompson Writing Studio This link opens in a new window
• Need to write a systematic review? This link opens in a new window

Contact a Librarian

Ask a Librarian

In the synthesis step of a literature review, researchers analyze and integrate information from selected sources to identify patterns and themes. This involves critically evaluating findings, recognizing commonalities, and constructing a cohesive narrative that contributes to the understanding of the research topic.

Here are some examples of how to approach synthesizing the literature:

💡 By themes or concepts

🕘 Historically or chronologically

📊 By methodology

These organizational approaches can also be used when writing your review. It can be beneficial to begin organizing your references by these approaches in your citation manager by using folders, groups, or collections.

Create a synthesis matrix

A synthesis matrix allows you to visually organize your literature.

Topic: ______________________________________________

Topic: Chemical exposure to workers in nail salons

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Writing a Literature Review: Organize, Synthesize, Evaluate

• Literature Review Process
• Literature Search
• Record your Search
• Organize, Synthesize, Evaluate
• Getting help

Table of Contents

On this page you will find:

Organizing Literature and Notes

How to scan an article.

• Reading for Comprehension
• Synthesis Matrix Information

Steps to take in organizing your literature and notes:

• Find common themes and organize the works into categories.
• Develop a subject level outline with studies you’ve found
• Expand or limit your search based on the information you found.
• How the works in each category relate to each other
• How the categories relate to each other and to your overall theme.

Available tools:

• Synthesis Matrix The "synthesis matrix" is an approach to organizing, monitoring, and documenting your search activities.
• Concept Mapping Concept Maps are graphic representations of topics, ideas, and their relationships. They allow users to group information in related modules so that the connections between and among the modules become more readily apparent than they might from an examination of a list. It can be done on paper or using specific software.
• Mind Mapping A mind map is a visual representation of hierarchical information that includes a central idea surrounded by connected branches of associated topics.
• NVIVO NVIVO is a qualitative data analysis software that can be applied for engineering literature review.

Synthesis Matrix

• Writing A Literature Review and Using a Synthesis Matrix Writing Center, Florida International University
• The Matrix Method of Literature Reviews Article from Health Promotion Practice journal.

Sample synthesis matrix

Synthesis matrix video

Skim the article to get the “big picture” for relevancy to your topic. You don’t have to understand every single idea in a text the first time you read it.

• Where was the paper published?
• What kind of journal it is? Is the journal peer-reviewed?
• Can you tell what the paper is about?
• Where are they from?
• What are the sections of the article?
• Are these clearly defined?  
• Can you figure out the purpose of the study, methodology, results and conclusion?
• Mentally review what you know about the topic
• Do you know enough to be able to understand the paper? If not, first read about the unfamiliar concepts  
• What is the overall context?
• Is the problem clearly stated?
• What does the paper bring new?
• Did it miss any previous major studies?
• Identify all the author’s assumptions.  
• Analyze the visuals for yourself and try to understand each of them. Make notes on what you understand. Write questions of what you do not understand. Make a guess about what materials/methods you expect to see. Do your own data interpretation and check them against the conclusions.  
• Do you agree with the author’s opinion?
• As you read, write down terms, techniques, unfamiliar concepts and look them up  
• Save retrieved sources to a reference manager

Read for Comprehension and Take Notes

Read for comprehension

• After first evaluation of sources, critically read the selected sources. Your goal is to determine how much of it to accept, determine its value, and decide whether you plan to include it in your literature review.
• Read the whole article, section by section but not necessarily in order and make sure you understand:

Introduction : What is known about the research and what is still unknown. Methods : What was measured? How was measured? Were the measurement appropriate? Did they offer sufficient evidence? Results : What is the main finding? Were there enough data presented? Were there problems not addressed? Discussions : Are these conclusions appropriate? Are there other factors that might have influenced? What does it need to be done to answer remaining questions?

• Find answers to your question from first step
• Formulate new questions and try to answer them
• Can you find any discrepancies? What would you have done differently?
• Re-read the whole article or just sections as many times you feel you need to
• When you believe that you have understood the article, write a summary in your own words (Make sure that there is nothing left that you cannot understand)

As you read, take (extensive) notes. Create your own system to take notes but be consistent. Remember that notes can be taken within the citation management tool.

What to write in your notes:

• identify key topic, methodology, key terms
• identify emphases, strengths, weaknesses, gaps (if any)
• determine relationships to other studies
• identify the relationship to your research topic
• new questions you have  
• suggestions for new directions, new sources to read
• everything else that seems relevant
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Synthesising the literature as part of a literature review

Affiliation.

• 1 University of Manchester, England.
• PMID: 25783281
• DOI: 10.7748/ns.29.29.44.e8957

This article examines how to synthesise and critique research literature. To place the process of synthesising the research literature into context, the article explores the critiquing process by breaking it down into seven sequential steps. The article explains how and why these steps need to be kept in mind if a robust comprehensive literature search and analysis are to be achieved. The article outlines how to engage in the critiquing process and explains how the literature review needs to be assembled to generate a logical and reasoned debate to examine a topic of interest or research in more detail.

Keywords: Critical analysis; critique; evaluation; integrative review; literature review; literature search; research; research question; search strategy; synthesis.

• Research / standards*
• Research Design*
• Review Literature as Topic*

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3.2 Synthesizing literature

Learning objectives.

• Connect the sources you read with key concepts in your research question and proposal
• Systematize the information and facts from each source you read

Putting the pieces together

Combining separate elements into a whole is the dictionary definition of synthesis. It is a way to make connections among and between numerous and varied source materials. A literature review is not an annotated bibliography, organized by title, author, or date of publication. Rather, it is grouped by topic and argument to create a whole view of the literature relevant to your research question.

Your synthesis must demonstrate a critical analysis of the papers you collected, as well as your ability to integrate the results of your analysis into your own literature review. Each source you collect should be critically evaluated and weighed based on the criteria from Chapter 2 before you include it in your review.

Begin the synthesis process by creating a grid, table, or an outline where you will summarize your literature review findings, using common themes you have identified and the sources you have found. The summary, grid, or outline will help you compare and contrast the themes, so you can see the relationships among them as well as areas where you may need to do more searching. A basic summary table is provided in Figure 3.2. Whichever method you choose, this type of organization will help you to both understand the information you find and structure the writing of your review. Remember, although “the means of summarizing can vary, the key at this point is to make sure you understand what you’ve found and how it relates to your topic and research question” (Bennard et al., 2014, para. 10).

As you read through the material you gather, look for common themes as they may provide the structure for your literature review. And, remember, writing a literature review is an iterative process. It is not unusual to go back and search academic databases for more sources of information as you read the articles you’ve collected.

Literature reviews can be organized sequentially or by topic, theme, method, results, theory, or argument. It’s important to develop categories that are meaningful and relevant to your research question. Take detailed notes on each article and use a consistent format for capturing all the information each article provides. These notes and the summary table can be done manually using note cards. However, given the amount of information you will be recording, an electronic file created in a word processing or spreadsheet (like this example Literature Search Template ) is more manageable. Examples of fields you may want to capture in your notes include:

• Authors’ names
• Article title
• Publication year
• Main purpose of the article
• Methodology or research design
• Participants
• Measurement
• Conclusions

Other fields that will be useful when you begin to synthesize the sum total of your research:

• Specific details of the article or research that are especially relevant to your study
• Key terms and definitions
• Strengths or weaknesses in research design
• Relationships to other studies
• Possible gaps in the research or literature (for example, many research articles conclude with the statement “more research is needed in this area”)
• Finally, note how closely each article relates to your topic. You may want to rank these as high, medium, or low relevance. For papers that you decide not to include, you may want to note your reasoning for exclusion, such as small sample size, local case study, or lacks evidence to support conclusions.

An example of how to organize summary tables by author or theme is shown in Table 3.1.

Here is an example summary table template .

Creating a topical outline

An alternative way to organize your articles for synthesis it to create an outline. After you have collected the articles you intend to use (and have put aside the ones you won’t be using), it’s time to extract as much as possible from the facts provided in those articles. You are starting your research project without a lot of hard facts on the topics you want to study, and by using the literature reviews provided in academic journal articles, you can gain a lot of knowledge about a topic in a short period of time.

As you read an article in detail, try copying the information you find relevant to your research topic in a separate word processing document. Copying and pasting from PDF to Word can be a pain because PDFs are image files not documents. To make that easier, use the HTML version of the article, convert the PDF to Word in Adobe Acrobat or another PDF reader, or use “paste special” command to paste the content into Word without formatting. If it’s an old PDF, you may have to simply type out the information you need. It can be a messy job, but having all of your facts in one place is very helpful for drafting your literature review.  Of course, you will not be using other authors’ words in your own literature review, but this is a good way to start compiling your notes.

You should copy and paste any fact or argument you consider important. Some good examples include definitions of concepts, statistics about the size of the social problem, and empirical evidence about the key variables in the research question, among countless others. It’s a good idea to consult with your professor and the syllabus for the course about what they are looking for when they read your literature review. Facts for your literature review are principally found in the introduction, results, and discussion section of an empirical article or at any point in a non-empirical article. Copy and paste into your notes anything you may want to use in your literature review.

Importantly, you must make sure you note the original source of that information. Nothing is worse than searching your articles for hours only to realize you forgot to note where your facts came from. If you found a statistic that the author used in the introduction, it almost certainly came from another source that the author cited in a footnote or internal citation. You will want to check the original source to make sure the author represented the information correctly. Moreover, you may want to read the original study to learn more about your topic and discover other sources relevant to your inquiry.

Assuming you have pulled all of the facts out of multiple articles, it’s time to start thinking about how these pieces of information relate to each other. Start grouping each fact into categories and subcategories as shown in Figure 3.3. For example, a statistic stating that homeless single adults are more likely to be male may fit into a category of gender and homelessness. For each topic or subtopic you identified during your critical analysis of each paper, determine what those papers have in common. Likewise, determine which ones in the group differ. If there are contradictory findings, you may be able to identify methodological or theoretical differences that could account for the contradiction. For example, one study may sample only high-income earners or those in a rural area. Determine what general conclusions you can report about the topic or subtopic, based on all of the information you’ve found.

Create a separate document containing a topical outline that combines your facts from each source and organizes them by topic or category. As you include more facts and more sources into your topical outline, you will begin to see how each fact fits into a category and how categories are related to each other. Your category names may change over time, as may their definitions. This is a natural reflection of the learning you are doing.

A complete topical outline is a long list of facts, arranged by category about your topic. As you step back from the outline, you should understand the topic areas where you have enough information to make strong conclusions about what the literature says. You should also assess in what areas you need to do more research before you can write a robust literature review. The topical outline should serve as a transitional document between the notes you write on each source and the literature review you submit to your professor. It is important to note that they contain plagiarized information that is copied and pasted directly from the primary sources. That’s okay because these are just notes and are not meant to be turned in as your own ideas. For your final literature review, you must paraphrase these sources to avoid plagiarism. More importantly, you should keep your voice and ideas front-and-center in what you write as this is your analysis of the literature. Make strong claims and support them thoroughly using facts you found in the literature. We will pick up the task of writing your literature review in section 3.3.

Additional resources for synthesizing literature

There are many ways to approach synthesizing literature. We’ve reviewed two examples here: summary tables and topical outlines. Other examples you may encounter include annotated bibliographies and synthesis matrices. As you are learning research, find a method that works for you. Reviewing the literature is a core component of evidence-based practice in social work at any level. See the resources below if you need some additional help:

Literature Reviews: Using a Matrix to Organize Research  / Saint Mary’s University of Minnesota

Literature Review: Synthesizing Multiple Sources  / Indiana University

Writing a Literature Review and Using a Synthesis Matrix  / Florida International University

Sample Literature Reviews Grid  / Complied by Lindsay Roberts

Killam, Laura (2013) . Literature review preparation: Creating a summary table . Includes transcript.

Key Takeaways

• It is necessary to take notes on research articles as you read. Try to develop a system that works for you to keep your notes organized, such as a summary table.
• Summary tables and topical outlines help researchers synthesize sources for the purpose of writing a literature review.

Image attributions

Pieces of the puzzle by congerdesign cc-0, adult diary by pexels cc-0.

• Figure 3.2 copied from Frederiksen, L. & Phelps, S. F. (2018). Literature reviews for education and nursing graduate students. Shared under a CC-BY 4.0 license. ↵
• This table was adapted from the work of Amanda Parsons ↵

Guidebook for Social Work Literature Reviews and Research Questions Copyright © 2020 by Rebecca Mauldin and Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Synthesizing Sources

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When you look for areas where your sources agree or disagree and try to draw broader conclusions about your topic based on what your sources say, you are engaging in synthesis. Writing a research paper usually requires synthesizing the available sources in order to provide new insight or a different perspective into your particular topic (as opposed to simply restating what each individual source says about your research topic).

Note that synthesizing is not the same as summarizing.  

• A summary restates the information in one or more sources without providing new insight or reaching new conclusions.
• A synthesis draws on multiple sources to reach a broader conclusion.

There are two types of syntheses: explanatory syntheses and argumentative syntheses . Explanatory syntheses seek to bring sources together to explain a perspective and the reasoning behind it. Argumentative syntheses seek to bring sources together to make an argument. Both types of synthesis involve looking for relationships between sources and drawing conclusions.

In order to successfully synthesize your sources, you might begin by grouping your sources by topic and looking for connections. For example, if you were researching the pros and cons of encouraging healthy eating in children, you would want to separate your sources to find which ones agree with each other and which ones disagree.

After you have a good idea of what your sources are saying, you want to construct your body paragraphs in a way that acknowledges different sources and highlights where you can draw new conclusions.

As you continue synthesizing, here are a few points to remember:

• Don’t force a relationship between sources if there isn’t one. Not all of your sources have to complement one another.
• Do your best to highlight the relationships between sources in very clear ways.
• Don’t ignore any outliers in your research. It’s important to take note of every perspective (even those that disagree with your broader conclusions).

Example Syntheses

Below are two examples of synthesis: one where synthesis is NOT utilized well, and one where it is.

Parents are always trying to find ways to encourage healthy eating in their children. Elena Pearl Ben-Joseph, a doctor and writer for KidsHealth , encourages parents to be role models for their children by not dieting or vocalizing concerns about their body image. The first popular diet began in 1863. William Banting named it the “Banting” diet after himself, and it consisted of eating fruits, vegetables, meat, and dry wine. Despite the fact that dieting has been around for over a hundred and fifty years, parents should not diet because it hinders children’s understanding of healthy eating.

In this sample paragraph, the paragraph begins with one idea then drastically shifts to another. Rather than comparing the sources, the author simply describes their content. This leads the paragraph to veer in an different direction at the end, and it prevents the paragraph from expressing any strong arguments or conclusions.

An example of a stronger synthesis can be found below.

Parents are always trying to find ways to encourage healthy eating in their children. Different scientists and educators have different strategies for promoting a well-rounded diet while still encouraging body positivity in children. David R. Just and Joseph Price suggest in their article “Using Incentives to Encourage Healthy Eating in Children” that children are more likely to eat fruits and vegetables if they are given a reward (855-856). Similarly, Elena Pearl Ben-Joseph, a doctor and writer for Kids Health , encourages parents to be role models for their children. She states that “parents who are always dieting or complaining about their bodies may foster these same negative feelings in their kids. Try to keep a positive approach about food” (Ben-Joseph). Martha J. Nepper and Weiwen Chai support Ben-Joseph’s suggestions in their article “Parents’ Barriers and Strategies to Promote Healthy Eating among School-age Children.” Nepper and Chai note, “Parents felt that patience, consistency, educating themselves on proper nutrition, and having more healthy foods available in the home were important strategies when developing healthy eating habits for their children.” By following some of these ideas, parents can help their children develop healthy eating habits while still maintaining body positivity.

In this example, the author puts different sources in conversation with one another. Rather than simply describing the content of the sources in order, the author uses transitions (like "similarly") and makes the relationship between the sources evident.

Synthesis and Making Connections for Strong Analysis

by acburton | Apr 25, 2024 | Resources for Students , Writing Resources

If Russian Dolls Aren’t For You, Here Are a Few Other Ways to Think About Synthesis

‘Joining the Conversation’: When we perform synthesis in our writing and engage with making connections, we are joining a wider conversation. We are seeing what has already been said about the topic, seeking out what these many perspectives and viewpoints have in common and/or how they differ, and then interpreting these relationships to form our own input to the conversation. We must directly engage with our sources to draw insightful conclusions and share what we think as a result. ‘Building the Bridge’: Synthesis is building the bridge between your sources for the reader. To synthesize or make connections, we must figure out how we get from one source to the other. In other words, we cannot present our sources in isolation (this wouldn’t help create any new meaning). Instead, we need to build the bridge between source A and source B so that our readers can understand what the two, together, suggest about our understanding of a topic. Then, we build a bridge from this new understanding to source C and source D, and so on.

Start Synthesizing

So you want to synthesize information? To start, review the existing literature on your selected topic. When searching for resources, aim to collect a number from various authors, subjects, and settings to broaden your understanding of the material – giving yourself more information to consider in the next stage. Ultimately, you’ll want to find the main idea presented in each source, as well as how the author supports or argues against it, as well as why.

• Compare and Contrast

Compare and contrast the main idea found in each source reviewed. What does each perspective have in common? What are their differences? Begin to consider how these sources  ‘fit together’ (or, in other words, build the bridge!). During this stage, you may find that some of your collected resources don’t have as much depth or go into as much detail as you’d like. That’s okay, but you’ll want to consider what effect this might have on your ability to draw a meaningful conclusion once synthesized with other source material.

• Ask, What’s the Significance?

By evaluating the quality and significance of each source, you can begin to consider its relevance within the context of your research or in relation to your topic. How does the relationship of one source to another further your understanding of the topic you are focusing on? What is the larger impact of what is being said or argued?

• Infer the Relationship and Draw Conclusions

By this point, you have gone through the existing literature surrounding your subject and compared/contrasted it, finding the main idea of each, as well as their intended purpose, possible criticisms, strengths, and weaknesses. Finally, you have related these ideas to your own research. Although you may have found that your sources agree or disagree on minor (or major) key details, it is the writer’s job to seek the relationship between these sources, put them in conversation together, and draw meaning through analysis. In some cases, you’ll be asked to offer your own perspective or argumentation. Consider, how might you add to the existing conversation?

Synthesis is all about meaningful connections, it is not summarizing sources side by side. Before you make larger claims about a topic, make sure you build those bridges between the sources you found through research. Nestle them together. Move beyond summary. Then, you can create an interesting and compelling argument. For additional help, make an appointment with the Writing Center!

Works Cited

Kourakos, Evanthia J. “The Matryoshka-Doll Effect.”  Medium , Azure’s Whereabouts, 22 Apr. 2016,  medium.com/azure-s- whereabouts/the-matryoshka- doll-effect-be9d2760d2e2 .Acces sed 25 Apr. 2024.

“Libguides: English Research: Synthesizing Information.”  Synthesizing Information – English Research – LibGuides at Aultman Health Sciences Library ,  aultman.libguides.com/c.php?g= 545558&p=7711993 . Accessed 25 Apr. 2024.

Writing in the Health and Social Sciences: Literature Reviews and Synthesis Tools

• Journal Publishing
• Style and Writing Guides
• Readings about Writing
• Citing in APA Style This link opens in a new window
• Resources for Dissertation Authors
• Citation Management and Formatting Tools
• What are Literature Reviews?
• Conducting & Reporting Systematic Reviews
• Finding Systematic Reviews
• Tutorials & Tools for Literature Reviews

Systematic Literature Reviews: Steps & Resources

These steps for conducting a systematic literature review are listed below . 

Also see subpages for more information about:

• The different types of literature reviews, including systematic reviews and other evidence synthesis methods
• Tools & Tutorials

Literature Review & Systematic Review Steps

• Develop a Focused Question
• Scope the Literature  (Initial Search)
• Refine & Expand the Search
• Limit the Results
• Download Citations
• Abstract & Analyze
• Create Flow Diagram
• Synthesize & Report Results

1. Develop a Focused   Question 

Consider the PICO Format: Population/Problem, Intervention, Comparison, Outcome

Focus on defining the Population or Problem and Intervention (don't narrow by Comparison or Outcome just yet!)

"What are the effects of the Pilates method for patients with low back pain?"

Tools & Additional Resources:

• PICO Question Help
• Stillwell, Susan B., DNP, RN, CNE; Fineout-Overholt, Ellen, PhD, RN, FNAP, FAAN; Melnyk, Bernadette Mazurek, PhD, RN, CPNP/PMHNP, FNAP, FAAN; Williamson, Kathleen M., PhD, RN Evidence-Based Practice, Step by Step: Asking the Clinical Question, AJN The American Journal of Nursing : March 2010 - Volume 110 - Issue 3 - p 58-61 doi: 10.1097/01.NAJ.0000368959.11129.79

2. Scope the Literature

A "scoping search" investigates the breadth and/or depth of the initial question or may identify a gap in the literature. 

Eligible studies may be located by searching in:

• Background sources (books, point-of-care tools)
• Article databases
• Trial registries
• Grey literature
• Cited references
• Reference lists

When searching, if possible, translate terms to controlled vocabulary of the database. Use text word searching when necessary.

Use Boolean operators to connect search terms:

• Combine separate concepts with AND  (resulting in a narrower search)
• Connecting synonyms with OR  (resulting in an expanded search)

Search:  pilates AND ("low back pain"  OR  backache )

Video Tutorials - Translating PICO Questions into Search Queries

• Translate Your PICO Into a Search in PubMed (YouTube, Carrie Price, 5:11) 
• Translate Your PICO Into a Search in CINAHL (YouTube, Carrie Price, 4:56)

3. Refine & Expand Your Search

Expand your search strategy with synonymous search terms harvested from:

• database thesauri
• reference lists
• relevant studies

Example: 

(pilates OR exercise movement techniques) AND ("low back pain" OR backache* OR sciatica OR lumbago OR spondylosis)

As you develop a final, reproducible strategy for each database, save your strategies in a:

• a personal database account (e.g., MyNCBI for PubMed)
• Log in with your NYU credentials
• Open and "Make a Copy" to create your own tracker for your literature search strategies

4. Limit Your Results

Use database filters to limit your results based on your defined inclusion/exclusion criteria.  In addition to relying on the databases' categorical filters, you may also need to manually screen results.  

• Limit to Article type, e.g.,:  "randomized controlled trial" OR multicenter study
• Limit by publication years, age groups, language, etc.

NOTE: Many databases allow you to filter to "Full Text Only".  This filter is  not recommended . It excludes articles if their full text is not available in that particular database (CINAHL, PubMed, etc), but if the article is relevant, it is important that you are able to read its title and abstract, regardless of 'full text' status. The full text is likely to be accessible through another source (a different database, or Interlibrary Loan).  

• Filters in PubMed
• CINAHL Advanced Searching Tutorial

5. Download Citations

Selected citations and/or entire sets of search results can be downloaded from the database into a citation management tool. If you are conducting a systematic review that will require reporting according to PRISMA standards, a citation manager can help you keep track of the number of articles that came from each database, as well as the number of duplicate records.

In Zotero, you can create a Collection for the combined results set, and sub-collections for the results from each database you search.  You can then use Zotero's 'Duplicate Items" function to find and merge duplicate records.

• Citation Managers - General Guide

6. Abstract and Analyze

• Migrate citations to data collection/extraction tool
• Screen Title/Abstracts for inclusion/exclusion
• Screen and appraise full text for relevance, methods, 
• Resolve disagreements by consensus

Covidence is a web-based tool that enables you to work with a team to screen titles/abstracts and full text for inclusion in your review, as well as extract data from the included studies.

• Covidence Support
• Critical Appraisal Tools
• Data Extraction Tools

7. Create Flow Diagram

The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) flow diagram is a visual representation of the flow of records through different phases of a systematic review.  It depicts the number of records identified, included and excluded.  It is best used in conjunction with the PRISMA checklist .

Example from: Stotz, S. A., McNealy, K., Begay, R. L., DeSanto, K., Manson, S. M., & Moore, K. R. (2021). Multi-level diabetes prevention and treatment interventions for Native people in the USA and Canada: A scoping review. Current Diabetes Reports, 2 (11), 46. https://doi.org/10.1007/s11892-021-01414-3

• PRISMA Flow Diagram Generator (ShinyApp.io, Haddaway et al. )
• PRISMA Diagram Templates  (Word and PDF)
• Make a copy of the file to fill out the template
• Image can be downloaded as PDF, PNG, JPG, or SVG
• Covidence generates a PRISMA diagram that is automatically updated as records move through the review phases

8. Synthesize & Report Results

There are a number of reporting guideline available to guide the synthesis and reporting of results in systematic literature reviews.

It is common to organize findings in a matrix, also known as a Table of Evidence (ToE).

• Reporting Guidelines for Systematic Reviews
• Download a sample template of a health sciences review matrix  (GoogleSheets)

Steps modified from: 

Cook, D. A., & West, C. P. (2012). Conducting systematic reviews in medical education: a stepwise approach.   Medical Education , 46 (10), 943–952.

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ChatGPT in higher education - a synthesis of the literature and a future research agenda

• Open access
• Published: 02 May 2024

Cite this article

You have full access to this open access article

• Pritpal Singh Bhullar 1 ,
• Mahesh Joshi 2 &
• Ritesh Chugh   ORCID: orcid.org/0000-0003-0061-7206 3  

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ChatGPT has emerged as a significant subject of research and exploration, casting a critical spotlight on teaching and learning practices in the higher education domain. This study examines the most influential articles, leading journals, and productive countries concerning citations and publications related to ChatGPT in higher education, while also shedding light on emerging thematic and geographic clusters within research on ChatGPT’s role and challenges in teaching and learning at higher education institutions. Forty-seven research papers from the Scopus database were shortlisted for bibliometric analysis. The findings indicate that the use of ChatGPT in higher education, particularly issues of academic integrity and research, has been studied extensively by scholars in the United States, who have produced the largest volume of publications, alongside the highest number of citations. This study uncovers four distinct thematic clusters (academic integrity, learning environment, student engagement, and scholarly research) and highlights the predominant areas of focus in research related to ChatGPT in higher education, including student examinations, academic integrity, student learning, and field-specific research, through a country-based bibliographic analysis. Plagiarism is a significant concern in the use of ChatGPT, which may reduce students’ ability to produce imaginative, inventive, and original material. This study offers valuable insights into the current state of ChatGPT in higher education literature, providing essential guidance for scholars, researchers, and policymakers.

Avoid common mistakes on your manuscript.

1 Introduction

ChatGPT, or Chat Generative Pre-trained Transformer, is a popular generative Artificial Intelligence (AI) chatbot developed by OpenAI, employing natural language processing to deliver interactive human-like conversational experiences (Jeon et al., 2023 ; Angelis et al., 2023 ). ChatGPT utilises a pre-trained language learning model, derived from an extensive big-data corpus, to predict outcomes based on a given prompt (Crawford et al., 2023 ; Geerling et al., 2023 ; Li et al., 2023 ). Since its inception, ChatGPT has attracted widespread attention and popularity and has the potential to disrupt the education sector (Rana, 2023 ). According to a research survey of adults conducted by the Pew Research Centre, approximately 60% of adults in the United States and 78% of adults in Asia possess knowledge of ChatGPT; furthermore, men are more familiar with ChatGPT than women (Vogels, 2023 ). The study also found that among ethnic groups globally, individuals of Asian descent have the highest level of familiarity with AI-based large language models (LLMs).

People have found value in using ChatGPT for a wide range of purposes, including generating creative content, answering questions, providing explanations, offering suggestions, and even having casual conversations (Crawford et al., 2023 ; Throp, 2023 ; Wu et al., 2023 ). Furthermore, ChatGPT is an effective digital assistant for facilitating a thorough understanding of diverse and intricate subjects using simple and accessible language. Given these features, ChatGPT has the potential to bring about a paradigm shift in traditional methods of delivering instruction and revolutionise the future of education (Tlili et al., 2023 ). ChatGPT stands out as a promising tool for open education, enhancing the independence and autonomy of autodidactic learners through personalised support, guidance, and feedback, potentially fostering increased motivation and engagement (Firat, 2023 ). Its capabilities encompass facilitating complex learning, asynchronous communication, feedback provision, and cognitive offloading (Memarian & Doleck, 2023 ).

However, the rapid expansion of ChatGPT has also aroused apprehensions in the academic world, particularly after reports surfaced that the New York Department of Education had unexpectedly imposed a ban on access to the tool due to concerns about academic integrity violations (Sun et al., 2023 ; Neumann et al., 2023 ; Crawford et al., 2023 ). Students who use ChatGPT to produce superior written assignments may have an unfair advantage over peers who lack access (Farrokhnia et al., 2023 ; Cotton et al., 2023 ). Ethical concerns about the deployment of LLMs include the potential for bias, effects on employment, misuse and unethical deployment, and loss of integrity. However, there has been little research on the potential dangers that a sophisticated chatbot such as ChatGPT poses in the realm of higher education, particularly through the lens of a systematic literature review and bibliometric techniques.

In this light, this paper explores the literature on the application of ChatGPT in higher education institutions and the obstacles encountered in various disciplines from the perspectives of both faculty and students. The paper aims to analyse the current state of the field by addressing the following overarching research questions using bibliographic coupling, co-occurrence analysis, citation analysis, and co-authorship analysis:

What are the most influential articles in terms of citations in research related to ChatGPT in education?

What are the top journals and countries in terms of publication productivity related to the implications of ChatGPT in higher education institutions?

What are the emerging thematic clusters in research on the role and challenges of ChatGPT in teaching and learning in higher education institutions?

What are the geographic clusters in research on the role and challenges of ChatGPT in teaching and learning in higher education institutions?

2 Methodology

In conducting this study, publications on the impact of ChatGPT on various aspects of higher education institutions were systematically identified through an extensive search using Elsevier’s Scopus database, a comprehensive repository hosting over 20,000 globally ranked, peer-reviewed journals (Mishra et al., 2017 ; Palomo et al., 2017 ; Vijaya & Mathur, 2023 ). Scopus is a widely used database for bibliometric analyses and is considered one of the “largest curated databases covering scientific journals” (pg. 5116) in different subject areas (Singh et al., 2021 ). Widely acclaimed for its comprehensive coverage, Scopus has been extensively employed in bibliometric analyses across diverse disciplines, as evidenced by studies in capital structure theories, business research, entrepreneurial orientation and blockchain security (Bajaj et al., 2020 ; Donthu et al., 2020 ; Gupta et al., 2021 ; Patrício & Ferreira, 2020 ). Notably, despite the “extremely high” correlation between the Web of Science and Scopus databases, Scopus’s status as a superior and versatile data source for literature extraction is reinforced by its broader coverage of subject areas and categories compared to the narrower journal scope of Web of Science, facilitating scholars in locating literature most pertinent to the review area (Archambault et al., 2009 ; Paul et al., 2021 ). To ensure a systematic literature review, we adhered to the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines (Page et al., 2021 ) for the search, identification, selection, reading, and data extraction from the articles retrieved through the Scopus database (Fig.  1 ). Reliance on a single database is acceptable within the PRISMA framework (Moher et al., 2009 ).

Employing Boolean-assisted search queries, we aimed to capture a comprehensive range of topics related to ChatGPT’s impact on higher education institutions. Specific search queries were carefully selected to ensure a broad yet relevant search scope and included the following:

“ChatGPT and Teaching learning in universities” OR “Effect of ChatGPT in higher education institution” OR “ChatGPT and student assessment in higher education” OR “ChatGPT and academic integrity” OR “ChatGPT and teaching pedagogy in higher education institution” OR “ChatGPT and cheating student course assignment” OR “ChatGPT and teaching in higher education” OR “Implications of ChatGPT in higher education institutions” OR “ChatGPT and evaluation criteria in higher education institution” OR “ChatGPT in universities” OR “ChatGPT and student learnings. ”

The study includes papers published and included in the Scopus database on or before May 26, 2023 on the theme of ChatGPT and higher education. This timeframe was chosen to encompass the most recent and relevant literature available up to the point of data retrieval. Papers identified through the search queries underwent inclusion or exclusion based on predetermined criteria. Specifically, only papers published in journals were considered for this study, as these undergo a peer-review process and are subject to stringent selection criteria set by the journals, ensuring their quality and reliability. Papers in conference proceedings were excluded from the start of the search. Only papers written in English were included to maintain consistency and clarity, whereas others were excluded. Of the 48 research papers that were initially identified, 47 were ultimately selected for the bibliometric analysis, which was conducted using VOSviewer, a bibliometric analysis tool.

PRISMA Flowchart

From the identified pool of 47 articles, the analysis uncovered a nuanced distribution of research methodologies. Specifically, 11 studies were grounded in quantitative research methodologies, underscoring a quantitative focus within the literature. In contrast, a substantial majority of 31 articles embraced a qualitative framework, showcasing a diverse spectrum that included pure qualitative research, editorials, letters to the editor, and opinion pieces. Furthermore, the review brought to light four literature reviews, signifying a synthesis of existing knowledge, and identified one study that strategically employed a mixed-methods approach, blending both qualitative and quantitative research techniques.

To address the research questions, the selected publications underwent analysis using various bibliometric techniques. For the first and second research questions, citation analysis was employed. For the third and fourth research questions, bibliographic analysis was performed in VOSviewer software to generate clusters.

3 Findings and discussion

3.1 publication trend.

Information from the Scopus database indicates that academics began focusing on investigating various aspects of ChatGPT’s potential in higher education in 2022, as they published their findings in 2023. All academic articles in reputable publications in the Scopus database were published in 2023.

3.2 Citation analysis

Table  1 presents the top ten articles according to the number of citations. The number of articles increased significantly in 2023, consistent with the emerging nature and growing relevance of the topic. Exploring the ramifications of ChatGPT in higher education is a recent focal point for scholars, with numerous aspects warranting deeper investigation. The limited citation count, as anticipated, underscores that publications from 2023 are in the early stages of gaining visibility and recognition within the academic community.

The article by Thorp ( 2023 ), entitled “ChatGPT is fun, but not an author”, has received the highest number of citations (79). Thorp stresses the risks associated with implementing ChatGPT in the classroom. Although ChatGPT is an innovative AI tool, significant barriers remain to its implementation in the field of education. According to Thorp, using ChatGPT in academic writing is still inefficient. Thorp also expresses concerns about the rising prevalence of ChatGPT in the fabrication of scientific publications. The second most-cited work, “How Does ChatGPT Perform on the United States Medical Licensing Examination?” by Gilson and colleagues, has received 27 citations. Gilson et al. ( 2023 ) evaluated the accuracy, speed and clarity of ChatGPT’s responses to questions on the United States Medical Licensing Examination’s Step 1 and Step 2 tests. The text responses generated by ChatGPT were evaluated using three qualitative metrics: the logical justification of the chosen answer, the inclusion of information relevant to the question, and the inclusion of information extraneous to the question. The model attained a level of proficiency comparable to that of a third-year medical student. The study demonstrates the potential utility of ChatGPT as an interactive educational resource in the field of medicine to facilitate the acquisition of knowledge and skills. Third is Kasneci et al.’s article “ChatGPT for good? On opportunities and challenges of large language models for education”, with 13 citations. This paper examines the benefits and drawbacks of using language models in the classroom from the perspectives of both teachers and students. The authors find that these comprehensive language models can serve as a supplement rather than a replacement for classroom instruction. Each of the remaining top-ten articles mentioned the impact of ChatGPT on academic integrity in education and had received fewer than ten citations at the time of analysis.

Table  2 presents the top 10 journals in terms of the number of citations of publications related to the topic of ChatGPT in higher education. The journal Science , which published “ChatGPT is fun, but not an author,” was deemed most influential because it received the highest number of citations (79). JMIR Medical Education has published two articles that have been cited by 30 other research articles on the same topic. Journal of University Teaching and Learning Practise has published the most articles: three. Innovations in Education and Teaching International has published two articles on this topic, which together have been cited by six articles.

As shown in Table  3 , the majority of research articles pertaining to ChatGPT and higher education have originated from countries in Asia. Six of the top 10 countries for publishing articles on this topic are located in the Asian continent. However, the most influential studies in terms of citations have been produced by the United States, Germany, Australia, and the United Kingdom. Combined, these countries have received a total of 63 citations, with individual counts of 36, 17, 7, and 7, respectively. These four countries have 90% of the total citations of the top 10 most productive countries in the field of research on higher education perspectives on ChatGPT.

3.3 Bibliographic coupling

3.3.1 thematic clusters.

Four thematic clusters (TCs) were identified from the included research articles, as shown in Table  4 . VOSviewer was used to perform clustering based on bibliographic coupling. This method identifies relations between documents by examining publications that cite the same sources (Boyack & Klavans, 2010 ). VOSviewer clusters articles with a common knowledge base, assigning each publication to exactly one cluster. To implement this clustering technique, we assessed the co-occurrence of bibliographic references among articles within our dataset. Co-occurrence was determined by identifying shared references between articles, indicating a thematic connection (Boyack & Klavans, 2010 ). Articles sharing common references were considered to co-occur, enabling us to quantify the extent of thematic relationships based on the frequency of shared references. We identified and categorised thematic clusters within our dataset through the combined approach of VOSviewer clustering and co-occurrence analysis. This method typically results in a distribution of clusters, with a limited number of larger clusters and a more substantial number of smaller clusters.

The clusters were derived through an analysis of subordinate articles extracted from the Scopus database. VOSviewer systematically organised similar articles into distinct clusters based on the shared patterns of bibliographic references (Van Eck & Waltman, 2010 ). To ensure methodological transparency and robustness, we established clear criteria and parameters for clustering. Specifically, keywords with a minimum frequency ( n  = 5) were included in the analysis, and co-occurrence was calculated based on a pairwise comparison method. This systematic approach ensured the meaningful representation of thematic relationships within the dataset, guided by insights from previous literature (Jarneving, 2007 ). Using cluster analysis techniques, the articles were organised into cohesive groups characterised by the degree of thematic homogeneity guided by the nature of the research findings. This approach ensured a robust representation of the underlying thematic structure (Jarneving, 2007 ).

Furthermore, to mitigate the risk of subjective bias in thematic categorisation, a counter-coding approach was employed. A second researcher independently categorised thematic clusters identified by VOSviewer to assess inter-rater agreement. The level of agreement between the two researchers was assessed using Cohen’s kappa coefficient, ensuring the reliability and validity of the thematic classification process. The resulting kappa coefficient (0.69) indicated substantial agreement, suggesting a high level of agreement beyond what would be expected by chance alone (Gisev et al., 2013 ). Furthermore, the nomenclature assigned to each cluster was finalised based on the predominant research theme emerging from the analysis, providing a concise and informative label for each group.

TC1: ChatGPT and Academic Integrity: Cotton et al. ( 2023 ) describe ChatGPT as a double-edged sword that potentially threatens academic integrity. AI essay writing systems are programmed to churn out essays based on specific guidelines or prompts, and it can be difficult to distinguish between human and machine-generated writing. Thus, students could potentially use these systems to cheat by submitting essays that are not their original work (Dehouche, 2021 ). Kasneci et al. ( 2023 ) argue that effective pedagogical practices must be developed in order to implement large language models in classrooms. These skills include not only a deep understanding of the technology but also an appreciation of its constraints and the vulnerability of complex systems in general. In addition, educational institutions need to develop a clearly articulated plan for the successful integration and optimal use of big language models in educational contexts and teaching curricula. In addition, students need to be taught how to verify information through a teaching strategy emphasising critical thinking effectively. Possible bias in the generated output, the need for continuous human supervision, and the likelihood of unforeseen effects are just a few of the challenges that come with the employment of AI systems. Continuous monitoring and transparency are necessary to ensure academic integrity while using ChatGPT. Lim et al. ( 2023 ) report that ChatGPT poses academic integrity challenges for the faculty of higher education institutions, who must verify whether academic work (assignments, research reports, etc.) submitted by students is derived from the fresh perspective of data analysis or plagiarised and recycled (copying and pasting original work) by ChatGPT. ChatGPT may threaten student learning and classroom engagement if students have access to information and course assignments without assessing their integrity. Perkins ( 2023 ) also expresses concerns regarding academic integrity in the use of ChatGPT. Students are utilising ChatGPT to complete their course assignments without attribution rather than producing original work. Higher education institutions must establish clear boundaries regarding academic integrity and plagiarism in light of the growing utilisation of AI tools in academic and research settings. In addition, the challenges posed by AI essay writing systems like ChatGPT necessitate a multifaceted approach to safeguard academic integrity. Educational institutions should invest in comprehensive educational programs that not only teach students the ethical use of technology but also incorporate rigorous assessments of critical thinking skills. Additionally, integrating AI literacy into the curriculum, with a focus on understanding the limitations and potential biases of big language models, can empower students to discern between human and machine-generated content.

TC2: ChatGPT and Learning Environment: According to Crawford et al. ( 2023 ), increased stress levels and peer pressure among university students have created a favourable environment for the use of AI tools. ChatGPT provides enhanced educational opportunities for college-level students. It can help students identify areas they may have overlooked, offer guidance on additional reading materials, and enhance existing peer and teacher connections. In addition, ChatGPT can propose alternative methods of evaluating students beyond conventional assignments. Crawford et al. ( 2023 ) recommend providing practical assignments incorporating ChatGPT as a supplementary tool to reduce plagiarism. Su ( 2023 ) documents that ChatGPT can provide students with a personalised learning experience based on their specific needs. In addition, the ChatGPT platform can be used to create a virtual coaching system that offers prompt feedback to educators during their classroom evaluations. This approach fosters critical thinking and supports early childhood educators in refining their teaching methodologies to optimise interactive learning outcomes for students. Tang ( 2023b ) proposes that bolstering research integrity can be achieved by imposing restrictions on the utilisation of NLP-generated content in research papers. Additionally, the author advocates for transparency from researchers, emphasising the importance of explicitly stating the proportion of NLP-generated content incorporated in their papers. This recommendation prompts a critical examination of the role of AI-generated content in scholarly work, emphasising the importance of nurturing independent research and writing skills for both students and researchers.

TC3: ChatGPT and Student Engagement: Lee ( 2023 ) examines the ability of ChatGPT to provide an interactive learning experience and boost student engagement beyond textbook pedagogy. Iskender ( 2023 ) explains that ChatGPT provides a mechanism for students to generate and investigate diverse concepts expeditiously, thereby helping them engage in imaginative and evaluative thinking on specific subject matter. This approach has the potential to optimise time management for students and allow them to concentrate on more advanced cognitive activities. AI tools such as ChatGPT can potentially enhance the personalisation of learning materials by providing visual aids and summaries that can aid the learning process and significantly improve students’ competencies. Hence, leveraging ChatGPT in education can revolutionise learning by facilitating interactive experiences, nurturing imaginative thinking, and optimising time management for students.

TC4: ChatGPT and Scholarly Research: Ivanov and Soliman ( 2023 ) and Yan ( 2023 ) focus on the practical applications and implications of LLMs like ChatGPT in educational settings and scholarly research within the context of language learning, writing, and tourism. Yan’s investigation into ChatGPT’s application in second-language writing examines its effectiveness in addressing specific writing tasks at the undergraduate level. The findings underscore the nuanced balance between the strengths of ChatGPT and the inherent limitations in handling demanding academic writing tasks. Nevertheless, ChatGPT is also labelled as an ‘all-in-one’ solution for scholarly research and writing (Yan, 2023 ). In parallel, Ivanov and Soliman ( 2023 ) highlight that ChatGPT can assist scholars in the field of tourism research by composing preliminary literature reviews, substantiating their chosen methodologies, and creating visual aids such as tables and charts. Furthermore, the researchers outline that ChatGPT could provide valuable methodological ideas and insights by helping researchers generate questions and corresponding scales for inclusion in questionnaires. Hence, ChatGPT has the potential to become a valuable ally as a facilitator in academic writing processes and has the potential to transform the research workflow.

3.3.2 Geographic clusters

The results of the country-based bibliographic analysis are summarised in Table  5 . The present study utilised the prevailing research theme in the existing literature as a framework for categorising the countries into four distinct clusters on the basis of the number of documents published from different countries.

Cluster 1: Implications of ChatGPT for Student Examinations and Education : Cluster 1 is composed of five countries: Germany, Ireland, South Korea, Taiwan, and the United States. Researchers in these countries have emphasised the potential role of ChatGPT in higher education within the context of AI language models. Eleven research articles related to this theme were published by researchers based in the United States, the most in this cluster. The top three articles in Table  1 are from the United States. The study entitled “Opportunities and Challenges of Large Language Models for Education,” was authored by German researchers (Kasneci et al., 2023 ) and has been widely cited in the academic community (13 citations). The remaining studies were conducted by researchers from South Korea and Taiwan and focused on the impact of ChatGPT on the education sector and its associated opportunities and challenges. This cluster demonstrates that students could benefit greatly from using ChatGPT in performing various academic tasks, such as reviewing and revising their work, verifying the accuracy of homework answers, and improving the quality of their essays. It has also aided postgraduates whose first language is not English improve their writing, as ChatGPT can be instructed to rewrite a paragraph in a scholarly tone from scratch. The outcomes have demonstrated significant efficacy, thereby alleviating the cognitive load associated with translation for these students, enabling them to concentrate on the substance of their writing rather than the intricacies of composing in an unfamiliar language. To harness the potential benefits, future research could focus on developing targeted training programs for students and educators that emphasise the effective utilisation of ChatGPT to enhance not only academic tasks but also language proficiency for non-native English speakers, addressing both cognitive load and language intricacies.

Cluster 2: ChatGPT and Academic Integrity : Cluster 2 comprises research studies conducted by authors from Japan, Bangladesh, Hong Kong, Nigeria, Pakistan, UAE, the UK, Vietnam and the Netherlands. The most influential study in this cluster, “Unlocking the power of ChatGPT: A framework for applying Generative AI in education”, was authored by researchers from Hong Kong (Su & Yang, 2023 ). They document that ChatGPT can be used to respond to student inquiries, reducing the time and effort required of educators and allowing them to focus their resources on other activities, such as scholarly investigations. Farrokhnia et al. ( 2023 ) and Yeadon et al. ( 2023 ) state that ChatGPT can write scientific abstracts with fabricated data and essays that can evade detection by reviewers. According to Liebrenz et al. ( 2023 ), ChatGPT tends to produce erroneous and incoherent responses, thereby raising the potential for disseminating inaccurate information in scholarly literature. The higher-order cognitive abilities of ChatGPT are relatively low, especially in areas related to creativity, critical thinking, reasoning, and problem-solving. ChatGPT could reduce students’ motivation to explore topics independently, draw their own conclusions, and solve problems independently (Kasneci et al., 2023 ). Ibrahim et al. ( 2023 ) find that ChatGPT can engage students in their academic pursuits. ChatGPT can enhance the writing abilities of non-native English speakers to allow them to concentrate on higher-order cognitive processes. This technological development allows faculty members to allocate more attention to conceptualisation and writing rather than focusing on the mechanics of grammar and spelling. However, there is a debate among intellectuals regarding the implications of AI for content creation, with some asserting that it detracts from innovative content development. The possibility that ChatGPT threatens academic honesty by facilitating essay plagiarism is being acknowledged. In addition, in the absence of appropriate citations, this textual content may violate copyright regulations. Cotton et al. ( 2023 ) express concerns about the potential impact of ChatGPT on academic integrity and plagiarism. Their work corroborates Dehouche’s ( 2021 ) assertion that students may use ChatGPT to engage in academic dishonesty by submitting essays that are not their original work. According to Cotton et al. ( 2023 ), ChatGPT users have a competitive advantage over non-users and can achieve higher grades on their coursework assignments by utilising the AI-based language tool. They classify ChatGPT as a versatile instrument with the potential to pose a threat to academic integrity, noting that AI essay writing systems are specifically programmed to generate content based on specific parameters or prompts, thereby challenging the discernment between human-authored and machine-generated content. Distinguishing between the academic work produced by students and the content of ChatGPT when evaluating assignments is a significant challenge for faculty. It is recommended that academic staff continually monitor student assignments for academic misconduct infractions, coupled with transparent communication about the potential risks associated with AI-generated content.

Cluster 3: ChatGPT and Students’ Learning : Cluster 3 comprises Malaysia, China and Australia. This cluster mainly includes studies of the role of AI-based models in student learning. Researchers from Australia (Crawford et al., 2023 ; Lim et al., 2023 ; Lawrie, 2023 ; Li et al., 2023 ; Seth et al., 2023 ; Cingillioglu, 2023 ; Skavronskaya, 2023 ; and Johinke, 2023 ) have contributed the most (8 studies) to this cluster and put their weight behind the role of AI and student learning in various disciplines. One of the most influential papers, “Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators”, was authored by researchers from both Australia and Malaysia (Lim et al., 2023 ) and reflected on the role of AI in classroom learning and teaching. Rather than banning AI tools, the authors advocate for the productive use of these tools in classrooms to facilitate more engaging student learning. Another Australian study titled, “Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI)” (Crawford et al., 2023 ) highlights AI as an alternative path of learning for students. ChatGPT can promptly evaluate students’ assignments and help them identify areas of weakness. Educators have the option to provide innovative assessments to their students instead of adhering solely to conventional assessments. ChatGPT can augment pedagogical approaches, evaluation structures, and the comprehensive educational milieu by reinforcing the trilateral association among instructors, learners, and technology. The implementation of ChatGPT can provide students with a personalised and interactive learning and research experience facilitated by virtual tutors and customised recommendations. In light of the research in this cluster, the integration of ChatGPT into education should inspire a paradigm shift towards a more dynamic and personalised learning environment. Institutions can explore strategic partnerships with AI researchers to develop context-specific applications of ChatGPT that cater to diverse educational needs, promoting a symbiotic relationship between human instructors, students, and technology for an enriched learning experience.

Cluster 4: ChatGPT and Field-specific Research : This cluster includes research by authors in Asian and European countries (India, Oman, Bulgaria and New Zealand) that has emphasised the potential role of ChatGPT in the medical and tourism industries. Authors from India explored the role of ChatGPT in the medical field (Seetharaman, 2023 ; Subramani et al., 2023 ). Seetharaman ( 2023 ) reports that ChatGPT offers supplementary language assistance to students who are not proficient in English, enabling them to enhance their language proficiency and effectively communicate in English, the principal language of instruction in medical establishments. The ChatGPT platform has the potential to serve as a tool for medical students to replicate patient interactions in a simulated environment, such as accurately obtaining medical histories and documenting symptoms. According to Subramani et al. ( 2023 ), ChatGPT is a highly efficient and user-friendly AI technology that can aid healthcare professionals in various aspects, such as diagnosis, critical decision-making, and devising appropriate treatment plans. ChatGPT has demonstrated impressive performance on medical exams, indicating its potential as a valuable resource for enhancing medical education and assessment (Subramani et al., 2023 ) and can support interdisciplinarity in tourism research (Nautiyal et al., 2023 ). Ivanov and Soliman ( 2023 ) note the potential of ChatGPT to serve as a digital instructor to provide students with enhanced and effective learning experiences and outcomes. Digital instructors can impart knowledge in diverse languages and thus can be used to educate individuals of varying nationalities and backgrounds in the field of tourism. Furthermore, LLM-based chatbots, including ChatGPT, can assess written assignments and provide direction on linguistic proficiency, syntax, and composition, ultimately enhancing students’ scholarly writing proficiency. In exploring the intersection of ChatGPT with medical education, institutions can pioneer innovative approaches by using the platform to create immersive, simulated patient interactions that go beyond language assistance, allowing medical students to practice nuanced skills such as medical history gathering and symptom documentation. Simultaneously, leveraging ChatGPT as a versatile digital instructor offers a unique opportunity to provide cross-cultural and multilingual education, contributing to a more inclusive and globally competent workforce within the tourism industry.

3.4 Challenges of ChatGPT in higher education

In addition to some previously mentioned challenges, such as the potential for plagiarism, the investigation also identified other key challenges in implementing ChatGPT within the context of higher education’s teaching and learning environment. Wu and Yu ( 2023 ) found that the benefits of AI-based ChatGPT are more in higher education as compared to primary and secondary education. The study also reported that the novelty effects of AI chatbots may enhance learning outcomes in brief interventions, but their efficacy diminishes in longer interventions.

First, the implementation of ChatGPT within the educational context engenders learning impediments. In the absence of adequate monitoring and regulation, the technology could lead to human unintelligence and unlearning, but teachers will become more adaptive and create authentic assessments to enhance student learning (Alafnan et al., 2023 ; Lawrie, 2023 ). Second, the technology could be used in a manner that violates students’ privacy. If the model is not adequately secured, it could surreptitiously gather confidential data from students without their explicit awareness or authorisation (Kanseci, 2023). Third, the technology could facilitate discrimination against particular students. If the model is not trained on a dataset that accurately represents the entire student population, it has the potential to create disparities in educational access (Cingillioglu, 2023 ; Lin et al., 2023 ). Fourth, according to Ivanov and Soloman (2023), ChatGPT lacks access to real-time data. Therefore, its responses may be inconsequential, inaccurate, or outdated. The information provided in response to a specific query may also be insufficient. Gao et al. (2022) highlight the need for further investigation of the precision and scholarly authenticity of ChatGPT. Fifth, it may be difficult for ChatGPT to comprehend the context and subtleties of complex academic subjects and answer complex questions (Adetayo, 2023 ; Eysenbach, 2023 ; Neumann et al., 2023 ). The system can misinterpret inquiries, offer inadequate or inaccurate responses, or struggle to comprehend the fundamental purpose behind questions (Clark, 2023 ). In particular, ChatGPT may not have the requisite expertise in highly specialised or advanced subjects such as advanced mathematics or specific sciences. Hence, it may not deliver precise and accurate answers (Neumann et al., 2023 ; Fergus et al., 2023 ). Karaali ( 2023 ) claimed that the primary emphasis in the field of AI is currently directed towards the enhancement of advanced cognitive abilities and mental processes associated with quantitative literacy and quantitative reasoning. However, it is important to acknowledge that fundamental skills such as writing, critical thinking, and numeracy continue to serve as essential foundational components among students. Although AI is making significant progress in fundamental domains, it appears that students are experiencing a decline in performance in the context of fundamental skills. Consequently, NLP-based adaptive learner support and education require further investigation (Bauer et al., 2023 ).

In addressing the challenges of ChatGPT in education, educators need to adapt and develop authentic assessments that mitigate the risk of human unlearning, ensuring that technology enhances, rather than hinders, student learning experiences. Simultaneously, recognising the limitations of ChatGPT in comprehending the nuances of highly specialised subjects underscores the importance of balancing advancements in AI’s cognitive abilities with continued emphasis on fundamental skills like critical thinking, writing, and numeracy, urging a reevaluation of priorities in AI-driven educational research towards comprehensive learner support.

4 Conclusion, implications and agenda for future research

This study identified the most influential articles and top journals and countries in terms of citations and publication productivity related to ChatGPT in higher education, as well as highlighted emerging thematic clusters and geographic clusters in research on the role and challenges of ChatGPT in teaching and learning in higher education institutions. Articles on the topic of ChatGPT in higher education published up to May 2023 were identified by searching the Scopus database. Given the emergent nature of ChatGPT starting in late 2022, all the included articles were published in 2023. Thus, this specific research domain remains relatively unexplored. The findings of this analysis reveal that the United States is the most productive country in terms of research on the role of ChatGPT in higher education, especially relating to academic integrity and research. US researchers also emerged as the most influential in terms of number of citations in the literature. Our findings corroborate those of previous research (Crompton & Burke, 2023 ). However, 60% of the articles in our shortlisted literature emanated from Asian countries.

Four thematic clusters (academic integrity, student engagement, learning environment and research) were identified. Furthermore, the country-based bibliographic analysis revealed that research has focused on student examinations, academic integrity, student learning and field-specific research in medical and tourism education (Nautiyal et al., 2023 ; Subramani et al., 2023 ). Plagiarism is recognised as a major challenge that hinders students’ creativity, innovativeness and originality when using ChatGPT in their academic pursuits. To mitigate the potential drawbacks of using ChatGPT in educational and research settings, proactive measures should be taken to educate students and researchers alike on the nature of plagiarism, its negative impacts and academic integrity (Shoufan, 2023 ; Teixeira, 2023 ) Educators may ask students to provide a written acknowledgement of the authenticity of their assignments and their non-reliance on ChatGPT. Such an acknowledgement would discourage students from utilising ChatGPT in their academic and research endeavours and establish accountability for their academic pursuits. In addition, educators should develop authentic assessments that are ChatGPT-proof.

ChatGPT lacks emotional intelligence and empathy, both of which are crucial in effectively addressing the emotional and psychological dimensions of the learning process (Farrokhnia et al., 2023 ; Neumann et al., 2023 ). Higher education institutions may encounter challenges in using ChatGPT to deliver suitable assistance, comprehension, or direction to students needing emotional or mental health support. The significance of human interaction in learning cannot be overstated. Achieving a balance between using AI and the advantages of human guidance and mentorship is a persistent challenge that requires attention (Neumann et al., 2023 ; Rahman et al., 2023 ). Strzelecki ( 2023 ) observed in his research that behavioural intention and personal innovativeness are the two major determinants behind the adoption of ChatGPT among students.

4.1 Implications

The findings of the present study have numerous important implications. This study provides insight into the current state of ChatGPT in higher education and thus can serve as valuable guidance for academics, practitioners, and policymakers. The study’s findings contribute to the literature by providing new insights into the role of ChatGPT and strategies for mitigating its negative aspects and emphasising its positive attributes.

First, the implementation of AI in education can improve academic performance and student motivation, particularly by facilitating personalised learning. Educational institutions should monitor and regulate students’ use of such technologies proactively. Higher education institutions also ought to prioritise the training of their educators in effectively utilising AI technologies, including ChatGPT. Concurrently, it is imperative for these institutions to equip students with comprehensive academic integrity training, shedding light on the appropriate and inappropriate applications of AI tools like ChatGPT. This includes creating awareness about the potential consequences of utilising these technologies for dishonest practices. Furthermore, educational establishments need to urgently revisit and refine their academic integrity policies to address the evolving landscape shaped by the integration of artificial intelligence tools in various academic facets. This proactive approach will foster a learning environment that embraces technological advancements and upholds the principles of honesty and responsible use. Institutional regulations on accountability and transparency should guide the frameworks that govern the use of AI in the campus environment (Pechenkina, 2023 ; Sun & Hoelscher, 2023 ; Dencik & Sanchez-Monedero, 2022 ).

Second, faculty members must proactively replace traditional coursework with modern alternatives that foster elevated levels of critical thinking among students, as suggested by Zhai ( 2022 ). Educators and learners can augment the academic material produced by ChatGPT with their own insights and information obtained from credible scholarly resources (Emenike & Emenike, 2023 ).

Third, ChatGPT should not be considered a threat to the education sector but a supplementary tool for human instruction that can enhance teaching and learning. It is imperative to acknowledge that the vital role of human educators cannot be replaced (Karaali, 2023 ) Moreover, ChatGPT can potentially enhance the accessibility and inclusivity of higher education. Alternative formats, linguistic support, and individualised explanations can help students who are studying English as a second language, are not native English speakers, or have other unique learning needs. Furthermore, Alnaqbi and Fouda ( 2023 ) highlight the implications of AI in evaluating the teaching style of faculty in higher education by collecting the feedback of students through social media and ChatGPT.

Fourth, the faculty in higher education institutions could address ethical concerns by providing students with explicit and comprehensive guidelines about the prescribed structure of academic assignments (Cotton et al., 2023 ; Gardner & Giordano, 2023 ). This practice can facilitate the production of more cohesive assignments. In addition, teachers can use rubrics to assess assignments and blend automated and manual assessment methodologies to evaluate students’ comprehension of the subject matter (Cotton et al., 2023 ; Shoufan, 2023 ).

In summary, using ChatGPT is recommended for enhancing creativity, refining writing proficiency, and improving research abilities. Nonetheless, it is crucial to emphasise that ChatGPT should not be employed as a substitute for critical thinking and producing original work. While it serves as a valuable tool for augmentation, upholding the integrity of independent thought and authentic content creation in academic endeavours is essential.

4.2 Limitations

The present study acknowledges several limitations. Firstly, the reliance on Scopus as the primary data source for bibliometric analysis may have limitations in capturing the full landscape of relevant literature. Future research may consider incorporating additional databases like Web of Science to ensure a comprehensive assessment. Secondly, due to the English language restriction in the review, potentially relevant studies may have been omitted. Future research could enhance inclusivity by extending its scope to encompass papers written in languages other than English. Thirdly, the current study exclusively focused on journal articles. Expanding the scope to include diverse sources, such as conference proceedings or book chapters, could offer a more comprehensive overview.

Additionally, as a rapidly evolving field, literature published after our inclusion dates need capturing, and future studies should consider adjusting their inclusion criteria to accommodate the dynamic nature of the subject matter. Lastly, the specificity of the bibliometric data search, centred around terms like ChatGPT, AI, higher education, and academic integrity, may have excluded certain relevant articles. Future studies should consider employing more generalised search parameters to encompass synonyms associated with these terms.

4.3 Future scope

The findings of the study suggest new avenues for future research. The effectiveness of evaluation criteria for assessments incorporating ChatGPT-generated text needs to be investigated. Specifically, the appropriate level of ChatGPT-produced text that students may use in academic tasks or assessments has not been established. Research on the ethical implications of using AI tools such as ChatGPT in higher education is also needed. Issues pertaining to data confidentiality, bias, and transparency in algorithms used for decision-making remain to be addressed. Feasible approaches for mitigating the excessive reliance of scholars and learners on ChatGPT or similar AI models are needed. Researchers could also explore the implementation of verification processes that go beyond traditional plagiarism detection methods, accounting for the unique challenges posed by AI systems. Future research in this domain could focus on establishing guidelines and best practices for the integration of AI tools like ChatGPT in academic settings, ensuring a balance between technological innovation and the preservation of academic rigour. Finally, the literature on ChatGPT in higher education has largely focused on the medical and tourism sectors. Future researchers must explore applications of ChatGPT in other disciplines.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.

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Bhullar, P.S., Joshi, M. & Chugh, R. ChatGPT in higher education - a synthesis of the literature and a future research agenda. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12723-x

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• hard to find studies, reports, or dissertations
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When conducting a systematic review it is important to include literature that has not formally been published in sources as it helps to prevent publication bias. Searching grey literature is supported/mandated by the Cochrane Collaboration , the Campbell Collaboration , JBI and the National Academy of Medicine (U.S.).

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• Search the Gray Literature Gateways listed in the next tab.
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• The report is a publication produced by the The New York Academy of Medicine between 1999 - 2016, alerting readers to new grey literature publications in health services research and selected urban health topics. As of January 2017, the Grey Literature Report website and database will be discontinued and will no longer be updated, but the resources will still be accessible. Grey Literature resources are cataloged and indexed using MeSH. The database allows full text keyword searching as well as subject searching and serves as an archive for the Reports.
• GreyNet International The goal of GreyNet is to facilitate dialog, research, and communication between persons and organisations in the field of grey literature. GreyNet further seeks to identify and distribute information on and about grey literature in networked environments. Its main activities include the International Conference Series on Grey Literature, the creation and maintenance of web-based resources, a moderated Listserv and combined Distribution List, The Grey Journal (TGJ), and curriculum development. Grey Literature is a field in library and Information science that deals with the production, distribution, and access to multiple document types produced on all levels of government, academics, business, and organization in electronic and print formats not controlled by commercial publishing i.e. where publishing is not the primary activity of the producing body. HP Labs, one of the pre-eminent industrial research laboratories in the world, is passionate about making our research real - driving technology to commercialization in the areas most important to our customers and society.
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• PubChem PubChem is an open chemistry database at the National Institutes of Health (NIH). “Open” means that you can put your scientific data in PubChem and that others may use it. Since the launch in 2004, PubChem has become a key chemical information resource for scientists, students, and the general public.
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Gray Lit and Regional Database Syntax

Search strategies for gray literature and regional databases often have to be distilled significantly from the main search strategy. This is due to the fact that many grey literature and regional databases cannot handle complex search strategies and special syntax. In addition, searching grey literature and regional databases with all the terms from the main search strategy sometimes returns far too many results to screen. The recommended method of simplifying a search strategy is to combine a few of the most important terms from each key concept of your research question. See an example below.

Research Question:  What is the effectiveness of  Vitamin B12   supplements in reducing morbidity in  pregnant women  with  HIV infection ?

• Key Concept 1 distilled terms : B12, B 12, cobalamin
• Key Concept 2 distilled terms:  pregnancy/pregnant, gestate/gestation/gestational
• Key Concept 3 distilled terms:  ​HIV, human immunodeficiency virus

Distilled Search Strategy:  (B12 OR "B 12" OR cobalamin) AND (pregnan* OR gestat*) AND (HIV OR "human immunodeficiency virus")

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May 2, 2024 by Gary Price

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Journal Article: “ChatGPT in Higher Education – A Synthesis Of The Literature And A Future Research Agenda”

The article linked below was published today by Education and Information Technologies.

ChatGPT in Higher Education – A Synthesis Of The Literature and a Future Research Agenda

Pritpal Singh Bhullar Maharaja Ranjit Singh Punjab Technical University, India

Mahesh Joshi RMIT University, Australia

Ritesh Chugh Central Queensland University, Australia

Education and Information Technologies (2024)

DOI: 10.1007/s10639-024-12723-x

ChatGPT has emerged as a significant subject of research and exploration, casting a critical spotlight on teaching and learning practices in the higher education domain. This study examines the most influential articles, leading journals, and productive countries concerning citations and publications related to ChatGPT in higher education, while also shedding light on emerging thematic and geographic clusters within research on ChatGPT’s role and challenges in teaching and learning at higher education institutions. Forty-seven research papers from the Scopus database were shortlisted for bibliometric analysis. The findings indicate that the use of ChatGPT in higher education, particularly issues of academic integrity and research, has been studied extensively by scholars in the United States, who have produced the largest volume of publications, alongside the highest number of citations. This study uncovers four distinct thematic clusters (academic integrity, learning environment, student engagement, and scholarly research) and highlights the predominant areas of focus in research related to ChatGPT in higher education, including student examinations, academic integrity, student learning, and field-specific research, through a country-based bibliographic analysis. Plagiarism is a significant concern in the use of ChatGPT, which may reduce students’ ability to produce imaginative, inventive, and original material. This study offers valuable insights into the current state of ChatGPT in higher education literature, providing essential guidance for scholars, researchers, and policymakers. Top 10 influential journals in terms of citations Source: 10.1007/s10639-024-12723-x

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About Gary Price

Gary Price ( [email protected] ) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.

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Updated geographic distributions for Texas reptiles

• Lawrence Bassett Texas State University, Austin, Texas
• Gregory Pandelis University of Texas at Arlington, Arlington, Texas

As is the case for many taxa in the Anthropocene, reptile conservation is challenged by an assortment of human-mediated factors. Distributional data for reptile species can be highly useful for informing conservation action. For example, species occurrence data can be used to model suitable habitat as well as quantify contraction, expansion, or shift in the distribution of a species. Texas, USA has a rich reptile fauna including one crocodilian, 32 testudine, 55 lacertilian, and 82 serpent species. However, literature pertaining to the distribution of these species has not been synthesized for over a decade. The goals of our study were to visually summarize all published distributional data for reptile species in the state with updated distribution maps; to tabulate all novel and historic distribution data that is absent from the last statewide synthesis; and to characterize any taxonomic, geographic, or temporal trends of distribution record reporting that have occurred in the state over the last decade. We discovered a total of 659 records that supplement the maps provided in the last statewide synthesis, 40% of which were found in published materials that predate that synthesis. Regarding distributional records published over the last decade, there was no apparent temporal trend – record reporting across years appeared to be stochastic. The number of records published for reptile families generally followed patterns of species richness, although several families had fewer or more records than would be expected. These results might be due to several factors including species biology, variable rates of potential range spread or contraction, and variable research attention (historically and contemporarily). Spatially, we found hot spots of record reporting in the southern, western, and northern portions of the state. We suspect these represent either a contemporary geographic bias of research attention, historically poor range characterization for reptile species occupying these regions, or a combination of both. We also found cold spots of record reporting in the northwestern portion of the Panhandle. These are likely due to natural patterns of reptile diversity as well as geographically biased research attention. Future work to be conducted on reptile distributions in Texas should include a thorough synthesis and revisiting of the voucher specimen data associated with these records.

Copyright (c) 2024 Lawrence Bassett, Gregory Pandelis

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License .

Copyright is held by the authors. Articles in R&A are made available under a Creative Commons Attribution-NonCommercial 4.0 International license.

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