what are advantages of literature review

Advantages and disadvantages of literature review

This comprehensive article explores some of the advantages and disadvantages of literature review in research. Reviewing relevant literature is a key area in research, and indeed, it is a research activity in itself. It helps researchers investigate a particular topic in detail. However, it has some limitations as well.

What is literature review?

In order to understand the advantages and disadvantages of literature review, it is important to understand what a literature review is and how it differs from other methods of research. According to Jones and Gratton (2009) a literature review essentially consists of critically reading, evaluating, and organising existing literature on a topic to assess the state of knowledge in the area. It is sometimes called critical review.

A literature review is a select analysis of existing research which is relevant to a researcher’s selected topic, showing how it relates to their investigation. It explains and justifies how their investigation may help answer some of the questions or gaps in the chosen area of study (University of Reading, 2022).

A literature review is a term used in the field of research to describe a systematic and methodical investigation of the relevant literature on a particular topic. In other words, it is an analysis of existing research on a topic in order to identify any relevant studies and draw conclusions about the topic.

A literature review is not the same as a bibliography or a database search. Rather than simply listing references to sources of information, a literature review involves critically evaluating and summarizing existing research on a topic. As such, it is a much more detailed and complex process than simply searching databases and websites, and it requires a lot of effort and skills.

Advantages of literature review

Information synthesis

A literature review is a very thorough and methodical exercise. It can be used to synthesize information and draw conclusions about a particular topic. Through a careful evaluation and critical summarization, researchers can draw a clear and comprehensive picture of the chosen topic.

Familiarity with the current knowledge

According to the University of Illinois (2022), literature reviews allow researchers to gain familiarity with the existing knowledge in their selected field, as well as the boundaries and limitations of that field.

Creation of new body of knowledge

One of the key advantages of literature review is that it creates new body of knowledge. Through careful evaluation and critical summarisation, researchers can create a new body of knowledge and enrich the field of study.

Answers to a range of questions

Literature reviews help researchers analyse the existing body of knowledge to determine the answers to a range of questions concerning a particular subject.

Disadvantages of literature review

Time consuming

As a literature review involves collecting and evaluating research and summarizing the findings, it requires a significant amount of time. To conduct a comprehensive review, researchers need to read many different articles and analyse a lot of data. This means that their review will take a long time to complete.

Lack of quality sources  

Researchers are expected to use a wide variety of sources of information to present a comprehensive review. However, it may sometimes be challenging for them to identify the quality sources because of the availability of huge numbers in their chosen field. It may also happen because of the lack of past empirical work, particularly if the selected topic is an unpopular one.

Descriptive writing

One of the major disadvantages of literature review is that instead of critical appreciation, some researchers end up developing reviews that are mostly descriptive. Their reviews are often more like summaries of the work of other writers and lack in criticality. It is worth noting that they must go beyond describing the literature.

Key features of literature review

Clear organisation

A literature review is typically a very critical and thorough process. Universities usually recommend students a particular structure to develop their reviews. Like all other academic writings, a review starts with an introduction and ends with a conclusion. Between the beginning and the end, researchers present the main body of the review containing the critical discussion of sources.

No obvious bias

A key feature of a literature review is that it should be very unbiased and objective. However, it should be mentioned that researchers may sometimes be influenced by their own opinions of the world.

Proper citation

One of the key features of literature review is that it must be properly cited. Researchers should include all the sources that they have used for information. They must do citations and provide a reference list by the end in line with a recognized referencing system such as Harvard.

To conclude this article, it can be said that a literature review is a type of research that seeks to examine and summarise existing research on a particular topic. It is an essential part of a dissertation/thesis. However, it is not an easy thing to handle by an inexperienced person. It also requires a lot of time and patience.

Hope you like this ‘Advantages and disadvantages of literature review’. Please share this with others to support our research work.

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Last update: 08 May 2022

References:

Jones, I., & Gratton, C. (2009) Research Methods for Sports Shttps://www.howandwhat.net/new/evaluate-website-content/tudies, 2 nd edition, London: Routledge

University of Illinois (2022) Literature review, available at: https://www.uis.edu/learning-hub/writing-resources/handouts/learning-hub/literature-review (accessed 08 May 2022)

University of Reading (2022) Literature reviews, available at: https://libguides.reading.ac.uk/literaturereview/starting (accessed 07 May 2022)

Author: M Rahman

M Rahman writes extensively online and offline with an emphasis on business management, marketing, and tourism. He is a lecturer in Management and Marketing. He holds an MSc in Tourism & Hospitality from the University of Sunderland. Also, graduated from Leeds Metropolitan University with a BA in Business & Management Studies and completed a DTLLS (Diploma in Teaching in the Life-Long Learning Sector) from London South Bank University.

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Conducting a Literature Review

Benefits of conducting a literature review.

• Steps in Conducting a Literature Review
• Summary of the Process
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• Literature Review Tutorial by American University Library
• The Literature Review: A Few Tips On Conducting It by University of Toronto
• Write a Literature Review by UC Santa Cruz University Library

While there might be many reasons for conducting a literature review, following are four key outcomes of doing the review.

Assessment of the current state of research on a topic . This is probably the most obvious value of the literature review. Once a researcher has determined an area to work with for a research project, a search of relevant information sources will help determine what is already known about the topic and how extensively the topic has already been researched.

Identification of the experts on a particular topic . One of the additional benefits derived from doing the literature review is that it will quickly reveal which researchers have written the most on a particular topic and are, therefore, probably the experts on the topic. Someone who has written twenty articles on a topic or on related topics is more than likely more knowledgeable than someone who has written a single article. This same writer will likely turn up as a reference in most of the other articles written on the same topic. From the number of articles written by the author and the number of times the writer has been cited by other authors, a researcher will be able to assume that the particular author is an expert in the area and, thus, a key resource for consultation in the current research to be undertaken.

Identification of key questions about a topic that need further research . In many cases a researcher may discover new angles that need further exploration by reviewing what has already been written on a topic. For example, research may suggest that listening to music while studying might lead to better retention of ideas, but the research might not have assessed whether a particular style of music is more beneficial than another. A researcher who is interested in pursuing this topic would then do well to follow up existing studies with a new study, based on previous research, that tries to identify which styles of music are most beneficial to retention.

Determination of methodologies used in past studies of the same or similar topics.  It is often useful to review the types of studies that previous researchers have launched as a means of determining what approaches might be of most benefit in further developing a topic. By the same token, a review of previously conducted studies might lend itself to researchers determining a new angle for approaching research.

Upon completion of the literature review, a researcher should have a solid foundation of knowledge in the area and a good feel for the direction any new research should take. Should any additional questions arise during the course of the research, the researcher will know which experts to consult in order to quickly clear up those questions.

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Literature Review: The What, Why and How-to Guide — Introduction

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What are Literature Reviews?

So, what is a literature review? "A literature review is an account of what has been published on a topic by accredited scholars and researchers. In writing the literature review, your purpose is to convey to your reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries." Taylor, D.  The literature review: A few tips on conducting it . University of Toronto Health Sciences Writing Centre.

Goals of Literature Reviews

What are the goals of creating a Literature Review?  A literature could be written to accomplish different aims:

• To develop a theory or evaluate an existing theory
• To summarize the historical or existing state of a research topic
• Identify a problem in a field of research 

Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews .  Review of General Psychology , 1 (3), 311-320.

What kinds of sources require a Literature Review?

• A research paper assigned in a course
• A thesis or dissertation
• A grant proposal
• An article intended for publication in a journal

All these instances require you to collect what has been written about your research topic so that you can demonstrate how your own research sheds new light on the topic.

Types of Literature Reviews

What kinds of literature reviews are written?

Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified. The review ends with a conclusion section which summarizes the findings regarding the state of the research of the specific study, the gaps identify and if applicable, explains how the author's research will address gaps identify in the review and expand the knowledge on the topic reviewed.

• Example : Predictors and Outcomes of U.S. Quality Maternity Leave: A Review and Conceptual Framework:  10.1177/08948453211037398  

Systematic review : "The authors of a systematic review use a specific procedure to search the research literature, select the studies to include in their review, and critically evaluate the studies they find." (p. 139). Nelson, L. K. (2013). Research in Communication Sciences and Disorders . Plural Publishing.

• Example : The effect of leave policies on increasing fertility: a systematic review:  10.1057/s41599-022-01270-w

Meta-analysis : "Meta-analysis is a method of reviewing research findings in a quantitative fashion by transforming the data from individual studies into what is called an effect size and then pooling and analyzing this information. The basic goal in meta-analysis is to explain why different outcomes have occurred in different studies." (p. 197). Roberts, M. C., & Ilardi, S. S. (2003). Handbook of Research Methods in Clinical Psychology . Blackwell Publishing.

• Example : Employment Instability and Fertility in Europe: A Meta-Analysis:  10.1215/00703370-9164737

Meta-synthesis : "Qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or related topic." (p.312). Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts .  Journal of Advanced Nursing , 53 (3), 311-318.

• Example : Women’s perspectives on career successes and barriers: A qualitative meta-synthesis:  10.1177/05390184221113735

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
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Conducting a literature review: why do a literature review, why do a literature review.

• How To Find "The Literature"
• Found it -- Now What?

Besides the obvious reason for students -- because it is assigned! -- a literature review helps you explore the research that has come before you, to see how your research question has (or has not) already been addressed.

You identify:

• core research in the field
• experts in the subject area
• methodology you may want to use (or avoid)
• gaps in knowledge -- or where your research would fit in

It Also Helps You:

• Publish and share your findings
• Justify requests for grants and other funding
• Identify best practices to inform practice
• Set wider context for a program evaluation
• Compile information to support community organizing

Great brief overview, from NCSU

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Literature Reviews

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Definition: A literature review is a systematic examination and synthesis of existing scholarly research on a specific topic or subject.

Purpose: It serves to provide a comprehensive overview of the current state of knowledge within a particular field.

Analysis: Involves critically evaluating and summarizing key findings, methodologies, and debates found in academic literature.

Identifying Gaps: Aims to pinpoint areas where there is a lack of research or unresolved questions, highlighting opportunities for further investigation.

Contextualization: Enables researchers to understand how their work fits into the broader academic conversation and contributes to the existing body of knowledge.

tl;dr  A literature review critically examines and synthesizes existing scholarly research and publications on a specific topic to provide a comprehensive understanding of the current state of knowledge in the field.

What is a literature review NOT?

❌ An annotated bibliography

❌ Original research

❌ A summary

❌ Something to be conducted at the end of your research

❌ An opinion piece

❌ A chronological compilation of studies

The reason for conducting a literature review is to:

Literature Reviews: An Overview for Graduate Students

While this 9-minute video from NCSU is geared toward graduate students, it is useful for anyone conducting a literature review.

Writing the literature review: A practical guide

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Literature reviews, what is a literature review, learning more about how to do a literature review.

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A literature review is a review and synthesis of existing research on a topic or research question. A literature review is meant to analyze the scholarly literature, make connections across writings and identify strengths, weaknesses, trends, and missing conversations. A literature review should address different aspects of a topic as it relates to your research question. A literature review goes beyond a description or summary of the literature you have read. 

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A literature review is not only a summary of key sources, but  has an organizational pattern which combines both summary and synthesis, often within specific conceptual categories . A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information in a way that informs how you are planning to investigate a research problem. The analytical features of a literature review might:

• Give a new interpretation of old material or combine new with old interpretations,
• Trace the intellectual progression of the field, including major debates,
• Depending on the situation, evaluate the sources and advise the reader on the most pertinent or relevant research, or
• Usually in the conclusion of a literature review, identify where gaps exist in how a problem has been researched to date.

The purpose of a literature review is to:

• Place each work in the context of its contribution to understanding the research problem being studied.
• Describe the relationship of each work to the others under consideration.
• Identify new ways to interpret prior research.
• Reveal any gaps that exist in the literature.
• Resolve conflicts amongst seemingly contradictory previous studies.
• Identify areas of prior scholarship to prevent duplication of effort.
• Point the way in fulfilling a need for additional research.
• Locate your own research within the context of existing literature [very important].
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What is the Purpose of a Literature Review?

4-minute read

• 23rd October 2023

If you’re writing a research paper or dissertation , then you’ll most likely need to include a comprehensive literature review . In this post, we’ll review the purpose of literature reviews, why they are so significant, and the specific elements to include in one. Literature reviews can:

1. Provide a foundation for current research.

2. Define key concepts and theories.

3. Demonstrate critical evaluation.

4. Show how research and methodologies have evolved.

5. Identify gaps in existing research.

6. Support your argument.

Keep reading to enter the exciting world of literature reviews!

What is a Literature Review?

A literature review is a critical summary and evaluation of the existing research (e.g., academic journal articles and books) on a specific topic. It is typically included as a separate section or chapter of a research paper or dissertation, serving as a contextual framework for a study. Literature reviews can vary in length depending on the subject and nature of the study, with most being about equal length to other sections or chapters included in the paper. Essentially, the literature review highlights previous studies in the context of your research and summarizes your insights in a structured, organized format. Next, let’s look at the overall purpose of a literature review.

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Literature reviews are considered an integral part of research across most academic subjects and fields. The primary purpose of a literature review in your study is to:

Provide a Foundation for Current Research

Since the literature review provides a comprehensive evaluation of the existing research, it serves as a solid foundation for your current study. It’s a way to contextualize your work and show how your research fits into the broader landscape of your specific area of study.  

Define Key Concepts and Theories

The literature review highlights the central theories and concepts that have arisen from previous research on your chosen topic. It gives your readers a more thorough understanding of the background of your study and why your research is particularly significant .

Demonstrate Critical Evaluation 

A comprehensive literature review shows your ability to critically analyze and evaluate a broad range of source material. And since you’re considering and acknowledging the contribution of key scholars alongside your own, it establishes your own credibility and knowledge.

Show How Research and Methodologies Have Evolved

Another purpose of literature reviews is to provide a historical perspective and demonstrate how research and methodologies have changed over time, especially as data collection methods and technology have advanced. And studying past methodologies allows you, as the researcher, to understand what did and did not work and apply that knowledge to your own research.  

Identify Gaps in Existing Research

Besides discussing current research and methodologies, the literature review should also address areas that are lacking in the existing literature. This helps further demonstrate the relevance of your own research by explaining why your study is necessary to fill the gaps.

Support Your Argument

A good literature review should provide evidence that supports your research questions and hypothesis. For example, your study may show that your research supports existing theories or builds on them in some way. Referencing previous related studies shows your work is grounded in established research and will ultimately be a contribution to the field.  

Literature Review Editing Services 

Ensure your literature review is polished and ready for submission by having it professionally proofread and edited by our expert team. Our literature review editing services will help your research stand out and make an impact. Not convinced yet? Send in your free sample today and see for yourself! 

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Literature Review

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What is it?

Literature reviews involve collecting information from literature that is already available, similar to a long essay. It is a written argument that builds a case from previous research (Machi and McEvoy, 2012). Every dissertation should include a literature review, but a dissertation as a whole can be a literature review. In this section we discuss literature reviews for the whole dissertation.

What are the benefits of a literature review?

There are advantages and disadvantages to any approach. The advantages of conducting a literature review include accessibility, deeper understanding of your chosen topic, identifying experts and current research within that area, and answering key questions about current research. The disadvantages might include not providing new information on the subject and, depending on the subject area, you may have to include information that is out of date.

How do I write it?

A literature review is often split into chapters, you can choose if these chapters have titles that represent the information within them, or call them chapter 1, chapter 2, ect. A regular format for a literature review is:

Introduction (including methodology)

This particular example is split into 6 sections, however it may be more or less depending on your topic.

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What is a literature review?

A literature review is an integrated analysis -- not just a summary-- of scholarly writings and other relevant evidence related directly to your research question.  That is, it represents a synthesis of the evidence that provides background information on your topic and shows a association between the evidence and your research question.

A literature review may be a stand alone work or the introduction to a larger research paper, depending on the assignment.  Rely heavily on the guidelines your instructor has given you.

Why is it important?

A literature review is important because it:

• Explains the background of research on a topic.
• Demonstrates why a topic is significant to a subject area.
• Discovers relationships between research studies/ideas.
• Identifies major themes, concepts, and researchers on a topic.
• Identifies critical gaps and points of disagreement.
• Discusses further research questions that logically come out of the previous studies.

APA7 Style resources

APA Style Blog - for those harder to find answers

1. Choose a topic. Define your research question.

Your literature review should be guided by your central research question.  The literature represents background and research developments related to a specific research question, interpreted and analyzed by you in a synthesized way.

• Make sure your research question is not too broad or too narrow.  Is it manageable?
• Begin writing down terms that are related to your question. These will be useful for searches later.
• If you have the opportunity, discuss your topic with your professor and your class mates.

2. Decide on the scope of your review

How many studies do you need to look at? How comprehensive should it be? How many years should it cover? 

• This may depend on your assignment.  How many sources does the assignment require?

3. Select the databases you will use to conduct your searches.

Make a list of the databases you will search. 

Where to find databases:

• use the tabs on this guide
• Find other databases in the Nursing Information Resources web page
• More on the Medical Library web page
• ... and more on the Yale University Library web page

4. Conduct your searches to find the evidence. Keep track of your searches.

• Use the key words in your question, as well as synonyms for those words, as terms in your search. Use the database tutorials for help.
• Save the searches in the databases. This saves time when you want to redo, or modify, the searches. It is also helpful to use as a guide is the searches are not finding any useful results.
• Review the abstracts of research studies carefully. This will save you time.
• Use the bibliographies and references of research studies you find to locate others.
• Check with your professor, or a subject expert in the field, if you are missing any key works in the field.
• Ask your librarian for help at any time.
• Use a citation manager, such as EndNote as the repository for your citations. See the EndNote tutorials for help.

Review the literature

Some questions to help you analyze the research:

• What was the research question of the study you are reviewing? What were the authors trying to discover?
• Was the research funded by a source that could influence the findings?
• What were the research methodologies? Analyze its literature review, the samples and variables used, the results, and the conclusions.
• Does the research seem to be complete? Could it have been conducted more soundly? What further questions does it raise?
• If there are conflicting studies, why do you think that is?
• How are the authors viewed in the field? Has this study been cited? If so, how has it been analyzed?

Tips: 

• Review the abstracts carefully.  
• Keep careful notes so that you may track your thought processes during the research process.
• Create a matrix of the studies for easy analysis, and synthesis, across all of the studies.
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What is a Literature Review?

A literature or narrative review is a comprehensive review and analysis of the published literature on a specific topic or research question. The literature that is reviewed contains: books, articles, academic articles, conference proceedings, association papers, and dissertations. It contains the most pertinent studies and points to important past and current research and practices. It provides background and context, and shows how your research will contribute to the field. 

A literature review should: 

• Provide a comprehensive and updated review of the literature;
• Explain why this review has taken place;
• Articulate a position or hypothesis;
• Acknowledge and account for conflicting and corroborating points of view

From  S age Research Methods

Purpose of a Literature Review

A literature review can be written as an introduction to a study to:

• Demonstrate how a study fills a gap in research
• Compare a study with other research that's been done

Or it can be a separate work (a research article on its own) which:

• Organizes or describes a topic
• Describes variables within a particular issue/problem

Limitations of a Literature Review

Some of the limitations of a literature review are:

• It's a snapshot in time. Unlike other reviews, this one has beginning, a middle and an end. There may be future developments that could make your work less relevant.
• It may be too focused. Some niche studies may miss the bigger picture.
• It can be difficult to be comprehensive. There is no way to make sure all the literature on a topic was considered.
• It is easy to be biased if you stick to top tier journals. There may be other places where people are publishing exemplary research. Look to open access publications and conferences to reflect a more inclusive collection. Also, make sure to include opposing views (and not just supporting evidence).

Source: Grant, Maria J., and Andrew Booth. “A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies.” Health Information & Libraries Journal, vol. 26, no. 2, June 2009, pp. 91–108. Wiley Online Library, doi:10.1111/j.1471-1842.2009.00848.x.

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Larayne Dallas : Engineering

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For help in other subject areas, please see the guide to library specialists by subject .

Periodically, UT Libraries runs a workshop covering the basics and library support for literature reviews. While we try to offer these once per academic year, we find providing the recording to be helpful to community members who have missed the session. Following is the most recent recording of the workshop, Conducting a Literature Review. To view the recording, a UT login is required.

• October 26, 2022 recording
• Last Updated: Oct 26, 2022 2:49 PM
• URL: https://guides.lib.utexas.edu/literaturereviews

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Literature Review

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The purpose of a literature review is to collect relevant, timely research on your chosen topic, and synthesize it into a cohesive summary of existing knowledge in the field. This then prepares you for making your own argument on that topic, or for conducting your own original research.

Depending on your field of study, literature reviews can take different forms. Some disciplines require that you synthesize your sources topically, organizing your paragraphs according to how your different sources discuss similar topics. Other disciplines require that you discuss each source in individual paragraphs, covering various aspects in that single article, chapter, or book.

Within your review of a given source, you can cover many different aspects, including (if a research study) the purpose, scope, methods, results, any discussion points, limitations, and implications for future research. Make sure you know which model your professor expects you to follow when writing your own literature reviews.

Tip : Literature reviews may or may not be a graded component of your class or major assignment, but even if it is not, it is a good idea to draft one so that you know the current conversations taking place on your chosen topic. It can better prepare you to write your own, unique argument.

Benefits of Literature Reviews

• Literature reviews allow you to gain familiarity with the current knowledge in your chosen field, as well as the boundaries and limitations of that field.
• Literature reviews also help you to gain an understanding of the theory(ies) driving the field, allowing you to place your research question into context.
• Literature reviews provide an opportunity for you to see and even evaluate successful and unsuccessful assessment and research methods in your field.
• Literature reviews prevent you from duplicating the same information as others writing in your field, allowing you to find your own, unique approach to your topic.
• Literature reviews give you familiarity with the knowledge in your field, giving you the chance to analyze the significance of your additional research.

Choosing Your Sources

When selecting your sources to compile your literature review, make sure you follow these guidelines to ensure you are working with the strongest, most appropriate sources possible.

Topically Relevant

Find sources within the scope of your topic

Appropriately Aged

Find sources that are not too old for your assignment

Find sources whose authors have authority on your topic

Appropriately “Published”

Find sources that meet your instructor’s guidelines (academic, professional, print, etc.)

Tip:  Treat your professors and librarians as experts you can turn to for advice on how to locate sources. They are a valuable asset to you, so take advantage of them!

Organizing Your Literature Review

Synthesizing topically.

Some assignments require discussing your sources together, in paragraphs organized according to shared topics between them.

For example, in a literature review covering current conversations on Alison Bechdel’s  Fun Home , authors may discuss various topics including:

• her graphic style
• her allusions to various literary texts
• her story’s implications regarding LGBT experiences in 20 th  century America.

In this case, you would cluster your sources on these three topics. One paragraph would cover how the sources you collected dealt with Bechdel’s graphic style. Another, her allusions. A third, her implications.

Each of these paragraphs would discuss how the sources you found treated these topics in connection to one another. Basically, you compare and contrast how your sources discuss similar issues and points.

To determine these shared topics, examine aspects including:

• Definition of terms
• Common ground
• Issues that divide
• Rhetorical context

Summarizing Individually

Depending on the assignment, your professor may prefer that you discuss each source in your literature review individually (in their own, separate paragraphs or sections). Your professor may give you specific guidelines as far as what to cover in these paragraphs/sections.

If, for instance, your sources are all primary research studies, here are some aspects to consider covering:

• Participants
• Limitations
• Implications
• Significance

Each section of your literature review, in this case, will identify all of these elements for each individual article.

You may or may not need to separate your information into multiple paragraphs for each source. If you do, using proper headings in the appropriate citation style (APA, MLA, etc.) will help keep you organized.

If you are writing a literature review as part of a larger assignment, you generally do not need an introduction and/or conclusion, because it is embedded within the context of your larger paper.

If, however, your literature review is a standalone assignment, it is a good idea to include some sort of introduction and conclusion to provide your reader with context regarding your topic, purpose, and any relevant implications or further questions. Make sure you know what your professor is expecting for your literature review’s content.

Typically, a literature review concludes with a full bibliography of your included sources. Make sure you use the style guide required by your professor for this assignment.

A systematic literature review of empirical research on ChatGPT in education

• Open access
• Published: 26 May 2024
• Volume 3 , article number  60 , ( 2024 )

Cite this article

You have full access to this open access article

• Yazid Albadarin   ORCID: orcid.org/0009-0005-8068-8902 1 ,
• Mohammed Saqr 1 ,
• Nicolas Pope 1 &
• Markku Tukiainen 1  

Over the last four decades, studies have investigated the incorporation of Artificial Intelligence (AI) into education. A recent prominent AI-powered technology that has impacted the education sector is ChatGPT. This article provides a systematic review of 14 empirical studies incorporating ChatGPT into various educational settings, published in 2022 and before the 10th of April 2023—the date of conducting the search process. It carefully followed the essential steps outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, as well as Okoli’s (Okoli in Commun Assoc Inf Syst, 2015) steps for conducting a rigorous and transparent systematic review. In this review, we aimed to explore how students and teachers have utilized ChatGPT in various educational settings, as well as the primary findings of those studies. By employing Creswell’s (Creswell in Educational research: planning, conducting, and evaluating quantitative and qualitative research [Ebook], Pearson Education, London, 2015) coding techniques for data extraction and interpretation, we sought to gain insight into their initial attempts at ChatGPT incorporation into education. This approach also enabled us to extract insights and considerations that can facilitate its effective and responsible use in future educational contexts. The results of this review show that learners have utilized ChatGPT as a virtual intelligent assistant, where it offered instant feedback, on-demand answers, and explanations of complex topics. Additionally, learners have used it to enhance their writing and language skills by generating ideas, composing essays, summarizing, translating, paraphrasing texts, or checking grammar. Moreover, learners turned to it as an aiding tool to facilitate their directed and personalized learning by assisting in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks. However, the results of specific studies (n = 3, 21.4%) show that overuse of ChatGPT may negatively impact innovative capacities and collaborative learning competencies among learners. Educators, on the other hand, have utilized ChatGPT to create lesson plans, generate quizzes, and provide additional resources, which helped them enhance their productivity and efficiency and promote different teaching methodologies. Despite these benefits, the majority of the reviewed studies recommend the importance of conducting structured training, support, and clear guidelines for both learners and educators to mitigate the drawbacks. This includes developing critical evaluation skills to assess the accuracy and relevance of information provided by ChatGPT, as well as strategies for integrating human interaction and collaboration into learning activities that involve AI tools. Furthermore, they also recommend ongoing research and proactive dialogue with policymakers, stakeholders, and educational practitioners to refine and enhance the use of AI in learning environments. This review could serve as an insightful resource for practitioners who seek to integrate ChatGPT into education and stimulate further research in the field.

Avoid common mistakes on your manuscript.

1 Introduction

Educational technology, a rapidly evolving field, plays a crucial role in reshaping the landscape of teaching and learning [ 82 ]. One of the most transformative technological innovations of our era that has influenced the field of education is Artificial Intelligence (AI) [ 50 ]. Over the last four decades, AI in education (AIEd) has gained remarkable attention for its potential to make significant advancements in learning, instructional methods, and administrative tasks within educational settings [ 11 ]. In particular, a large language model (LLM), a type of AI algorithm that applies artificial neural networks (ANNs) and uses massively large data sets to understand, summarize, generate, and predict new content that is almost difficult to differentiate from human creations [ 79 ], has opened up novel possibilities for enhancing various aspects of education, from content creation to personalized instruction [ 35 ]. Chatbots that leverage the capabilities of LLMs to understand and generate human-like responses have also presented the capacity to enhance student learning and educational outcomes by engaging students, offering timely support, and fostering interactive learning experiences [ 46 ].

The ongoing and remarkable technological advancements in chatbots have made their use more convenient, increasingly natural and effortless, and have expanded their potential for deployment across various domains [ 70 ]. One prominent example of chatbot applications is the Chat Generative Pre-Trained Transformer, known as ChatGPT, which was introduced by OpenAI, a leading AI research lab, on November 30th, 2022. ChatGPT employs a variety of deep learning techniques to generate human-like text, with a particular focus on recurrent neural networks (RNNs). Long short-term memory (LSTM) allows it to grasp the context of the text being processed and retain information from previous inputs. Also, the transformer architecture, a neural network architecture based on the self-attention mechanism, allows it to analyze specific parts of the input, thereby enabling it to produce more natural-sounding and coherent output. Additionally, the unsupervised generative pre-training and the fine-tuning methods allow ChatGPT to generate more relevant and accurate text for specific tasks [ 31 , 62 ]. Furthermore, reinforcement learning from human feedback (RLHF), a machine learning approach that combines reinforcement learning techniques with human-provided feedback, has helped improve ChatGPT’s model by accelerating the learning process and making it significantly more efficient.

This cutting-edge natural language processing (NLP) tool is widely recognized as one of today's most advanced LLMs-based chatbots [ 70 ], allowing users to ask questions and receive detailed, coherent, systematic, personalized, convincing, and informative human-like responses [ 55 ], even within complex and ambiguous contexts [ 63 , 77 ]. ChatGPT is considered the fastest-growing technology in history: in just three months following its public launch, it amassed an estimated 120 million monthly active users [ 16 ] with an estimated 13 million daily queries [ 49 ], surpassing all other applications [ 64 ]. This remarkable growth can be attributed to the unique features and user-friendly interface that ChatGPT offers. Its intuitive design allows users to interact seamlessly with the technology, making it accessible to a diverse range of individuals, regardless of their technical expertise [ 78 ]. Additionally, its exceptional performance results from a combination of advanced algorithms, continuous enhancements, and extensive training on a diverse dataset that includes various text sources such as books, articles, websites, and online forums [ 63 ], have contributed to a more engaging and satisfying user experience [ 62 ]. These factors collectively explain its remarkable global growth and set it apart from predecessors like Bard, Bing Chat, ERNIE, and others.

In this context, several studies have explored the technological advancements of chatbots. One noteworthy recent research effort, conducted by Schöbel et al. [ 70 ], stands out for its comprehensive analysis of more than 5,000 studies on communication agents. This study offered a comprehensive overview of the historical progression and future prospects of communication agents, including ChatGPT. Moreover, other studies have focused on making comparisons, particularly between ChatGPT and alternative chatbots like Bard, Bing Chat, ERNIE, LaMDA, BlenderBot, and various others. For example, O’Leary [ 53 ] compared two chatbots, LaMDA and BlenderBot, with ChatGPT and revealed that ChatGPT outperformed both. This superiority arises from ChatGPT’s capacity to handle a wider range of questions and generate slightly varied perspectives within specific contexts. Similarly, ChatGPT exhibited an impressive ability to formulate interpretable responses that were easily understood when compared with Google's feature snippet [ 34 ]. Additionally, ChatGPT was compared to other LLMs-based chatbots, including Bard and BERT, as well as ERNIE. The findings indicated that ChatGPT exhibited strong performance in the given tasks, often outperforming the other models [ 59 ].

Furthermore, in the education context, a comprehensive study systematically compared a range of the most promising chatbots, including Bard, Bing Chat, ChatGPT, and Ernie across a multidisciplinary test that required higher-order thinking. The study revealed that ChatGPT achieved the highest score, surpassing Bing Chat and Bard [ 64 ]. Similarly, a comparative analysis was conducted to compare ChatGPT with Bard in answering a set of 30 mathematical questions and logic problems, grouped into two question sets. Set (A) is unavailable online, while Set (B) is available online. The results revealed ChatGPT's superiority in Set (A) over Bard. Nevertheless, Bard's advantage emerged in Set (B) due to its capacity to access the internet directly and retrieve answers, a capability that ChatGPT does not possess [ 57 ]. However, through these varied assessments, ChatGPT consistently highlights its exceptional prowess compared to various alternatives in the ever-evolving chatbot technology.

The widespread adoption of chatbots, especially ChatGPT, by millions of students and educators, has sparked extensive discussions regarding its incorporation into the education sector [ 64 ]. Accordingly, many scholars have contributed to the discourse, expressing both optimism and pessimism regarding the incorporation of ChatGPT into education. For example, ChatGPT has been highlighted for its capabilities in enriching the learning and teaching experience through its ability to support different learning approaches, including adaptive learning, personalized learning, and self-directed learning [ 58 , 60 , 91 ]), deliver summative and formative feedback to students and provide real-time responses to questions, increase the accessibility of information [ 22 , 40 , 43 ], foster students’ performance, engagement and motivation [ 14 , 44 , 58 ], and enhance teaching practices [ 17 , 18 , 64 , 74 ].

On the other hand, concerns have been also raised regarding its potential negative effects on learning and teaching. These include the dissemination of false information and references [ 12 , 23 , 61 , 85 ], biased reinforcement [ 47 , 50 ], compromised academic integrity [ 18 , 40 , 66 , 74 ], and the potential decline in students' skills [ 43 , 61 , 64 , 74 ]. As a result, ChatGPT has been banned in multiple countries, including Russia, China, Venezuela, Belarus, and Iran, as well as in various educational institutions in India, Italy, Western Australia, France, and the United States [ 52 , 90 ].

Clearly, the advent of chatbots, especially ChatGPT, has provoked significant controversy due to their potential impact on learning and teaching. This indicates the necessity for further exploration to gain a deeper understanding of this technology and carefully evaluate its potential benefits, limitations, challenges, and threats to education [ 79 ]. Therefore, conducting a systematic literature review will provide valuable insights into the potential prospects and obstacles linked to its incorporation into education. This systematic literature review will primarily focus on ChatGPT, driven by the aforementioned key factors outlined above.

However, the existing literature lacks a systematic literature review of empirical studies. Thus, this systematic literature review aims to address this gap by synthesizing the existing empirical studies conducted on chatbots, particularly ChatGPT, in the field of education, highlighting how ChatGPT has been utilized in educational settings, and identifying any existing gaps. This review may be particularly useful for researchers in the field and educators who are contemplating the integration of ChatGPT or any chatbot into education. The following research questions will guide this study:

What are students' and teachers' initial attempts at utilizing ChatGPT in education?

What are the main findings derived from empirical studies that have incorporated ChatGPT into learning and teaching?

2 Methodology

To conduct this study, the authors followed the essential steps of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) and Okoli’s [ 54 ] steps for conducting a systematic review. These included identifying the study’s purpose, drafting a protocol, applying a practical screening process, searching the literature, extracting relevant data, evaluating the quality of the included studies, synthesizing the studies, and ultimately writing the review. The subsequent section provides an extensive explanation of how these steps were carried out in this study.

2.1 Identify the purpose

Given the widespread adoption of ChatGPT by students and teachers for various educational purposes, often without a thorough understanding of responsible and effective use or a clear recognition of its potential impact on learning and teaching, the authors recognized the need for further exploration of ChatGPT's impact on education in this early stage. Therefore, they have chosen to conduct a systematic literature review of existing empirical studies that incorporate ChatGPT into educational settings. Despite the limited number of empirical studies due to the novelty of the topic, their goal is to gain a deeper understanding of this technology and proactively evaluate its potential benefits, limitations, challenges, and threats to education. This effort could help to understand initial reactions and attempts at incorporating ChatGPT into education and bring out insights and considerations that can inform the future development of education.

2.2 Draft the protocol

The next step is formulating the protocol. This protocol serves to outline the study process in a rigorous and transparent manner, mitigating researcher bias in study selection and data extraction [ 88 ]. The protocol will include the following steps: generating the research question, predefining a literature search strategy, identifying search locations, establishing selection criteria, assessing the studies, developing a data extraction strategy, and creating a timeline.

2.3 Apply practical screen

The screening step aims to accurately filter the articles resulting from the searching step and select the empirical studies that have incorporated ChatGPT into educational contexts, which will guide us in answering the research questions and achieving the objectives of this study. To ensure the rigorous execution of this step, our inclusion and exclusion criteria were determined based on the authors' experience and informed by previous successful systematic reviews [ 21 ]. Table 1 summarizes the inclusion and exclusion criteria for study selection.

2.4 Literature search

We conducted a thorough literature search to identify articles that explored, examined, and addressed the use of ChatGPT in Educational contexts. We utilized two research databases: Dimensions.ai, which provides access to a large number of research publications, and lens.org, which offers access to over 300 million articles, patents, and other research outputs from diverse sources. Additionally, we included three databases, Scopus, Web of Knowledge, and ERIC, which contain relevant research on the topic that addresses our research questions. To browse and identify relevant articles, we used the following search formula: ("ChatGPT" AND "Education"), which included the Boolean operator "AND" to get more specific results. The subject area in the Scopus and ERIC databases were narrowed to "ChatGPT" and "Education" keywords, and in the WoS database was limited to the "Education" category. The search was conducted between the 3rd and 10th of April 2023, which resulted in 276 articles from all selected databases (111 articles from Dimensions.ai, 65 from Scopus, 28 from Web of Science, 14 from ERIC, and 58 from Lens.org). These articles were imported into the Rayyan web-based system for analysis. The duplicates were identified automatically by the system. Subsequently, the first author manually reviewed the duplicated articles ensured that they had the same content, and then removed them, leaving us with 135 unique articles. Afterward, the titles, abstracts, and keywords of the first 40 manuscripts were scanned and reviewed by the first author and were discussed with the second and third authors to resolve any disagreements. Subsequently, the first author proceeded with the filtering process for all articles and carefully applied the inclusion and exclusion criteria as presented in Table  1 . Articles that met any one of the exclusion criteria were eliminated, resulting in 26 articles. Afterward, the authors met to carefully scan and discuss them. The authors agreed to eliminate any empirical studies solely focused on checking ChatGPT capabilities, as these studies do not guide us in addressing the research questions and achieving the study's objectives. This resulted in 14 articles eligible for analysis.

2.5 Quality appraisal

The examination and evaluation of the quality of the extracted articles is a vital step [ 9 ]. Therefore, the extracted articles were carefully evaluated for quality using Fink’s [ 24 ] standards, which emphasize the necessity for detailed descriptions of methodology, results, conclusions, strengths, and limitations. The process began with a thorough assessment of each study's design, data collection, and analysis methods to ensure their appropriateness and comprehensive execution. The clarity, consistency, and logical progression from data to results and conclusions were also critically examined. Potential biases and recognized limitations within the studies were also scrutinized. Ultimately, two articles were excluded for failing to meet Fink’s criteria, particularly in providing sufficient detail on methodology, results, conclusions, strengths, or limitations. The review process is illustrated in Fig.  1 .

The study selection process

2.6 Data extraction

The next step is data extraction, the process of capturing the key information and categories from the included studies. To improve efficiency, reduce variation among authors, and minimize errors in data analysis, the coding categories were constructed using Creswell's [ 15 ] coding techniques for data extraction and interpretation. The coding process involves three sequential steps. The initial stage encompasses open coding , where the researcher examines the data, generates codes to describe and categorize it, and gains a deeper understanding without preconceived ideas. Following open coding is axial coding , where the interrelationships between codes from open coding are analyzed to establish more comprehensive categories or themes. The process concludes with selective coding , refining and integrating categories or themes to identify core concepts emerging from the data. The first coder performed the coding process, then engaged in discussions with the second and third authors to finalize the coding categories for the first five articles. The first coder then proceeded to code all studies and engaged again in discussions with the other authors to ensure the finalization of the coding process. After a comprehensive analysis and capturing of the key information from the included studies, the data extraction and interpretation process yielded several themes. These themes have been categorized and are presented in Table  2 . It is important to note that open coding results were removed from Table  2 for aesthetic reasons, as it included many generic aspects, such as words, short phrases, or sentences mentioned in the studies.

2.7 Synthesize studies

In this stage, we will gather, discuss, and analyze the key findings that emerged from the selected studies. The synthesis stage is considered a transition from an author-centric to a concept-centric focus, enabling us to map all the provided information to achieve the most effective evaluation of the data [ 87 ]. Initially, the authors extracted data that included general information about the selected studies, including the author(s)' names, study titles, years of publication, educational levels, research methodologies, sample sizes, participants, main aims or objectives, raw data sources, and analysis methods. Following that, all key information and significant results from the selected studies were compiled using Creswell’s [ 15 ] coding techniques for data extraction and interpretation to identify core concepts and themes emerging from the data, focusing on those that directly contributed to our research questions and objectives, such as the initial utilization of ChatGPT in learning and teaching, learners' and educators' familiarity with ChatGPT, and the main findings of each study. Finally, the data related to each selected study were extracted into an Excel spreadsheet for data processing. The Excel spreadsheet was reviewed by the authors, including a series of discussions to ensure the finalization of this process and prepare it for further analysis. Afterward, the final result being analyzed and presented in various types of charts and graphs. Table 4 presents the extracted data from the selected studies, with each study labeled with a capital 'S' followed by a number.

This section consists of two main parts. The first part provides a descriptive analysis of the data compiled from the reviewed studies. The second part presents the answers to the research questions and the main findings of these studies.

3.1 Part 1: descriptive analysis

This section will provide a descriptive analysis of the reviewed studies, including educational levels and fields, participants distribution, country contribution, research methodologies, study sample size, study population, publication year, list of journals, familiarity with ChatGPT, source of data, and the main aims and objectives of the studies. Table 4 presents a comprehensive overview of the extracted data from the selected studies.

3.1.1 The number of the reviewed studies and publication years

The total number of the reviewed studies was 14. All studies were empirical studies and published in different journals focusing on Education and Technology. One study was published in 2022 [S1], while the remaining were published in 2023 [S2]-[S14]. Table 3 illustrates the year of publication, the names of the journals, and the number of reviewed studies published in each journal for the studies reviewed.

3.1.2 Educational levels and fields

The majority of the reviewed studies, 11 studies, were conducted in higher education institutions [S1]-[S10] and [S13]. Two studies did not specify the educational level of the population [S12] and [S14], while one study focused on elementary education [S11]. However, the reviewed studies covered various fields of education. Three studies focused on Arts and Humanities Education [S8], [S11], and [S14], specifically English Education. Two studies focused on Engineering Education, with one in Computer Engineering [S2] and the other in Construction Education [S3]. Two studies focused on Mathematics Education [S5] and [S12]. One study focused on Social Science Education [S13]. One study focused on Early Education [S4]. One study focused on Journalism Education [S9]. Finally, three studies did not specify the field of education [S1], [S6], and [S7]. Figure  2 represents the educational levels in the reviewed studies, while Fig.  3 represents the context of the reviewed studies.

Educational levels in the reviewed studies

Context of the reviewed studies

3.1.3 Participants distribution and countries contribution

The reviewed studies have been conducted across different geographic regions, providing a diverse representation of the studies. The majority of the studies, 10 in total, [S1]-[S3], [S5]-[S9], [S11], and [S14], primarily focused on participants from single countries such as Pakistan, the United Arab Emirates, China, Indonesia, Poland, Saudi Arabia, South Korea, Spain, Tajikistan, and the United States. In contrast, four studies, [S4], [S10], [S12], and [S13], involved participants from multiple countries, including China and the United States [S4], China, the United Kingdom, and the United States [S10], the United Arab Emirates, Oman, Saudi Arabia, and Jordan [S12], Turkey, Sweden, Canada, and Australia [ 13 ]. Figures  4 and 5 illustrate the distribution of participants, whether from single or multiple countries, and the contribution of each country in the reviewed studies, respectively.

The reviewed studies conducted in single or multiple countries

The Contribution of each country in the studies

3.1.4 Study population and sample size

Four study populations were included: university students, university teachers, university teachers and students, and elementary school teachers. Six studies involved university students [S2], [S3], [S5] and [S6]-[S8]. Three studies focused on university teachers [S1], [S4], and [S6], while one study specifically targeted elementary school teachers [S11]. Additionally, four studies included both university teachers and students [S10] and [ 12 , 13 , 14 ], and among them, study [S13] specifically included postgraduate students. In terms of the sample size of the reviewed studies, nine studies included a small sample size of less than 50 participants [S1], [S3], [S6], [S8], and [S10]-[S13]. Three studies had 50–100 participants [S2], [S9], and [S14]. Only one study had more than 100 participants [S7]. It is worth mentioning that study [S4] adopted a mixed methods approach, including 10 participants for qualitative analysis and 110 participants for quantitative analysis.

3.1.5 Participants’ familiarity with using ChatGPT

The reviewed studies recruited a diverse range of participants with varying levels of familiarity with ChatGPT. Five studies [S2], [S4], [S6], [S8], and [S12] involved participants already familiar with ChatGPT, while eight studies [S1], [S3], [S5], [S7], [S9], [S10], [S13] and [S14] included individuals with differing levels of familiarity. Notably, one study [S11] had participants who were entirely unfamiliar with ChatGPT. It is important to note that four studies [S3], [S5], [S9], and [S11] provided training or guidance to their participants before conducting their studies, while ten studies [S1], [S2], [S4], [S6]-[S8], [S10], and [S12]-[S14] did not provide training due to the participants' existing familiarity with ChatGPT.

3.1.6 Research methodology approaches and source(S) of data

The reviewed studies adopted various research methodology approaches. Seven studies adopted qualitative research methodology [S1], [S4], [S6], [S8], [S10], [S11], and [S12], while three studies adopted quantitative research methodology [S3], [S7], and [S14], and four studies employed mixed-methods, which involved a combination of both the strengths of qualitative and quantitative methods [S2], [S5], [S9], and [S13].

In terms of the source(s) of data, the reviewed studies obtained their data from various sources, such as interviews, questionnaires, and pre-and post-tests. Six studies relied on interviews as their primary source of data collection [S1], [S4], [S6], [S10], [S11], and [S12], four studies relied on questionnaires [S2], [S7], [S13], and [S14], two studies combined the use of pre-and post-tests and questionnaires for data collection [S3] and [S9], while two studies combined the use of questionnaires and interviews to obtain the data [S5] and [S8]. It is important to note that six of the reviewed studies were quasi-experimental [S3], [S5], [S8], [S9], [S12], and [S14], while the remaining ones were experimental studies [S1], [S2], [S4], [S6], [S7], [S10], [S11], and [S13]. Figures  6 and 7 illustrate the research methodologies and the source (s) of data used in the reviewed studies, respectively.

Research methodologies in the reviewed studies

Source of data in the reviewed studies

3.1.7 The aim and objectives of the studies

The reviewed studies encompassed a diverse set of aims, with several of them incorporating multiple primary objectives. Six studies [S3], [S6], [S7], [S8], [S11], and [S12] examined the integration of ChatGPT in educational contexts, and four studies [S4], [S5], [S13], and [S14] investigated the various implications of its use in education, while three studies [S2], [S9], and [S10] aimed to explore both its integration and implications in education. Additionally, seven studies explicitly explored attitudes and perceptions of students [S2] and [S3], educators [S1] and [S6], or both [S10], [S12], and [S13] regarding the utilization of ChatGPT in educational settings.

3.2 Part 2: research questions and main findings of the reviewed studies

This part will present the answers to the research questions and the main findings of the reviewed studies, classified into two main categories (learning and teaching) according to AI Education classification by [ 36 ]. Figure  8 summarizes the main findings of the reviewed studies in a visually informative diagram. Table 4 provides a detailed list of the key information extracted from the selected studies that led to generating these themes.

The main findings in the reviewed studies

4 Students' initial attempts at utilizing ChatGPT in learning and main findings from students' perspective

4.1 virtual intelligent assistant.

Nine studies demonstrated that ChatGPT has been utilized by students as an intelligent assistant to enhance and support their learning. Students employed it for various purposes, such as answering on-demand questions [S2]-[S5], [S8], [S10], and [S12], providing valuable information and learning resources [S2]-[S5], [S6], and [S8], as well as receiving immediate feedback [S2], [S4], [S9], [S10], and [S12]. In this regard, students generally were confident in the accuracy of ChatGPT's responses, considering them relevant, reliable, and detailed [S3], [S4], [S5], and [S8]. However, some students indicated the need for improvement, as they found that answers are not always accurate [S2], and that misleading information may have been provided or that it may not always align with their expectations [S6] and [S10]. It was also observed by the students that the accuracy of ChatGPT is dependent on several factors, including the quality and specificity of the user's input, the complexity of the question or topic, and the scope and relevance of its training data [S12]. Many students felt that ChatGPT's answers were not always accurate and most of them believed that it requires good background knowledge to work with.

4.2 Writing and language proficiency assistant

Six of the reviewed studies highlighted that ChatGPT has been utilized by students as a valuable assistant tool to improve their academic writing skills and language proficiency. Among these studies, three mainly focused on English education, demonstrating that students showed sufficient mastery in using ChatGPT for generating ideas, summarizing, paraphrasing texts, and completing writing essays [S8], [S11], and [S14]. Furthermore, ChatGPT helped them in writing by making students active investigators rather than passive knowledge recipients and facilitated the development of their writing skills [S11] and [S14]. Similarly, ChatGPT allowed students to generate unique ideas and perspectives, leading to deeper analysis and reflection on their journalism writing [S9]. In terms of language proficiency, ChatGPT allowed participants to translate content into their home languages, making it more accessible and relevant to their context [S4]. It also enabled them to request changes in linguistic tones or flavors [S8]. Moreover, participants used it to check grammar or as a dictionary [S11].

4.3 Valuable resource for learning approaches

Five studies demonstrated that students used ChatGPT as a valuable complementary resource for self-directed learning. It provided learning resources and guidance on diverse educational topics and created a supportive home learning environment [S2] and [S4]. Moreover, it offered step-by-step guidance to grasp concepts at their own pace and enhance their understanding [S5], streamlined task and project completion carried out independently [S7], provided comprehensive and easy-to-understand explanations on various subjects [S10], and assisted in studying geometry operations, thereby empowering them to explore geometry operations at their own pace [S12]. Three studies showed that students used ChatGPT as a valuable learning resource for personalized learning. It delivered age-appropriate conversations and tailored teaching based on a child's interests [S4], acted as a personalized learning assistant, adapted to their needs and pace, which assisted them in understanding mathematical concepts [S12], and enabled personalized learning experiences in social sciences by adapting to students' needs and learning styles [S13]. On the other hand, it is important to note that, according to one study [S5], students suggested that using ChatGPT may negatively affect collaborative learning competencies between students.

4.4 Enhancing students' competencies

Six of the reviewed studies have shown that ChatGPT is a valuable tool for improving a wide range of skills among students. Two studies have provided evidence that ChatGPT led to improvements in students' critical thinking, reasoning skills, and hazard recognition competencies through engaging them in interactive conversations or activities and providing responses related to their disciplines in journalism [S5] and construction education [S9]. Furthermore, two studies focused on mathematical education have shown the positive impact of ChatGPT on students' problem-solving abilities in unraveling problem-solving questions [S12] and enhancing the students' understanding of the problem-solving process [S5]. Lastly, one study indicated that ChatGPT effectively contributed to the enhancement of conversational social skills [S4].

4.5 Supporting students' academic success

Seven of the reviewed studies highlighted that students found ChatGPT to be beneficial for learning as it enhanced learning efficiency and improved the learning experience. It has been observed to improve students' efficiency in computer engineering studies by providing well-structured responses and good explanations [S2]. Additionally, students found it extremely useful for hazard reporting [S3], and it also enhanced their efficiency in solving mathematics problems and capabilities [S5] and [S12]. Furthermore, by finding information, generating ideas, translating texts, and providing alternative questions, ChatGPT aided students in deepening their understanding of various subjects [S6]. It contributed to an increase in students' overall productivity [S7] and improved efficiency in composing written tasks [S8]. Regarding learning experiences, ChatGPT was instrumental in assisting students in identifying hazards that they might have otherwise overlooked [S3]. It also improved students' learning experiences in solving mathematics problems and developing abilities [S5] and [S12]. Moreover, it increased students' successful completion of important tasks in their studies [S7], particularly those involving average difficulty writing tasks [S8]. Additionally, ChatGPT increased the chances of educational success by providing students with baseline knowledge on various topics [S10].

5 Teachers' initial attempts at utilizing ChatGPT in teaching and main findings from teachers' perspective

5.1 valuable resource for teaching.

The reviewed studies showed that teachers have employed ChatGPT to recommend, modify, and generate diverse, creative, organized, and engaging educational contents, teaching materials, and testing resources more rapidly [S4], [S6], [S10] and [S11]. Additionally, teachers experienced increased productivity as ChatGPT facilitated quick and accurate responses to questions, fact-checking, and information searches [S1]. It also proved valuable in constructing new knowledge [S6] and providing timely answers to students' questions in classrooms [S11]. Moreover, ChatGPT enhanced teachers' efficiency by generating new ideas for activities and preplanning activities for their students [S4] and [S6], including interactive language game partners [S11].

5.2 Improving productivity and efficiency

The reviewed studies showed that participants' productivity and work efficiency have been significantly enhanced by using ChatGPT as it enabled them to allocate more time to other tasks and reduce their overall workloads [S6], [S10], [S11], [S13], and [S14]. However, three studies [S1], [S4], and [S11], indicated a negative perception and attitude among teachers toward using ChatGPT. This negativity stemmed from a lack of necessary skills to use it effectively [S1], a limited familiarity with it [S4], and occasional inaccuracies in the content provided by it [S10].

5.3 Catalyzing new teaching methodologies

Five of the reviewed studies highlighted that educators found the necessity of redefining their teaching profession with the assistance of ChatGPT [S11], developing new effective learning strategies [S4], and adapting teaching strategies and methodologies to ensure the development of essential skills for future engineers [S5]. They also emphasized the importance of adopting new educational philosophies and approaches that can evolve with the introduction of ChatGPT into the classroom [S12]. Furthermore, updating curricula to focus on improving human-specific features, such as emotional intelligence, creativity, and philosophical perspectives [S13], was found to be essential.

5.4 Effective utilization of CHATGPT in teaching

According to the reviewed studies, effective utilization of ChatGPT in education requires providing teachers with well-structured training, support, and adequate background on how to use ChatGPT responsibly [S1], [S3], [S11], and [S12]. Establishing clear rules and regulations regarding its usage is essential to ensure it positively impacts the teaching and learning processes, including students' skills [S1], [S4], [S5], [S8], [S9], and [S11]-[S14]. Moreover, conducting further research and engaging in discussions with policymakers and stakeholders is indeed crucial for the successful integration of ChatGPT in education and to maximize the benefits for both educators and students [S1], [S6]-[S10], and [S12]-[S14].

6 Discussion

The purpose of this review is to conduct a systematic review of empirical studies that have explored the utilization of ChatGPT, one of today’s most advanced LLM-based chatbots, in education. The findings of the reviewed studies showed several ways of ChatGPT utilization in different learning and teaching practices as well as it provided insights and considerations that can facilitate its effective and responsible use in future educational contexts. The results of the reviewed studies came from diverse fields of education, which helped us avoid a biased review that is limited to a specific field. Similarly, the reviewed studies have been conducted across different geographic regions. This kind of variety in geographic representation enriched the findings of this review.

In response to RQ1 , "What are students' and teachers' initial attempts at utilizing ChatGPT in education?", the findings from this review provide comprehensive insights. Chatbots, including ChatGPT, play a crucial role in supporting student learning, enhancing their learning experiences, and facilitating diverse learning approaches [ 42 , 43 ]. This review found that this tool, ChatGPT, has been instrumental in enhancing students' learning experiences by serving as a virtual intelligent assistant, providing immediate feedback, on-demand answers, and engaging in educational conversations. Additionally, students have benefited from ChatGPT’s ability to generate ideas, compose essays, and perform tasks like summarizing, translating, paraphrasing texts, or checking grammar, thereby enhancing their writing and language competencies. Furthermore, students have turned to ChatGPT for assistance in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks, which fosters a supportive home learning environment, allowing them to take responsibility for their own learning and cultivate the skills and approaches essential for supportive home learning environment [ 26 , 27 , 28 ]. This finding aligns with the study of Saqr et al. [ 68 , 69 ] who highlighted that, when students actively engage in their own learning process, it yields additional advantages, such as heightened motivation, enhanced achievement, and the cultivation of enthusiasm, turning them into advocates for their own learning.

Moreover, students have utilized ChatGPT for tailored teaching and step-by-step guidance on diverse educational topics, streamlining task and project completion, and generating and recommending educational content. This personalization enhances the learning environment, leading to increased academic success. This finding aligns with other recent studies [ 26 , 27 , 28 , 60 , 66 ] which revealed that ChatGPT has the potential to offer personalized learning experiences and support an effective learning process by providing students with customized feedback and explanations tailored to their needs and abilities. Ultimately, fostering students' performance, engagement, and motivation, leading to increase students' academic success [ 14 , 44 , 58 ]. This ultimate outcome is in line with the findings of Saqr et al. [ 68 , 69 ], which emphasized that learning strategies are important catalysts of students' learning, as students who utilize effective learning strategies are more likely to have better academic achievement.

Teachers, too, have capitalized on ChatGPT's capabilities to enhance productivity and efficiency, using it for creating lesson plans, generating quizzes, providing additional resources, generating and preplanning new ideas for activities, and aiding in answering students’ questions. This adoption of technology introduces new opportunities to support teaching and learning practices, enhancing teacher productivity. This finding aligns with those of Day [ 17 ], De Castro [ 18 ], and Su and Yang [ 74 ] as well as with those of Valtonen et al. [ 82 ], who revealed that emerging technological advancements have opened up novel opportunities and means to support teaching and learning practices, and enhance teachers’ productivity.

In response to RQ2 , "What are the main findings derived from empirical studies that have incorporated ChatGPT into learning and teaching?", the findings from this review provide profound insights and raise significant concerns. Starting with the insights, chatbots, including ChatGPT, have demonstrated the potential to reshape and revolutionize education, creating new, novel opportunities for enhancing the learning process and outcomes [ 83 ], facilitating different learning approaches, and offering a range of pedagogical benefits [ 19 , 43 , 72 ]. In this context, this review found that ChatGPT could open avenues for educators to adopt or develop new effective learning and teaching strategies that can evolve with the introduction of ChatGPT into the classroom. Nonetheless, there is an evident lack of research understanding regarding the potential impact of generative machine learning models within diverse educational settings [ 83 ]. This necessitates teachers to attain a high level of proficiency in incorporating chatbots, such as ChatGPT, into their classrooms to create inventive, well-structured, and captivating learning strategies. In the same vein, the review also found that teachers without the requisite skills to utilize ChatGPT realized that it did not contribute positively to their work and could potentially have adverse effects [ 37 ]. This concern could lead to inequity of access to the benefits of chatbots, including ChatGPT, as individuals who lack the necessary expertise may not be able to harness their full potential, resulting in disparities in educational outcomes and opportunities. Therefore, immediate action is needed to address these potential issues. A potential solution is offering training, support, and competency development for teachers to ensure that all of them can leverage chatbots, including ChatGPT, effectively and equitably in their educational practices [ 5 , 28 , 80 ], which could enhance accessibility and inclusivity, and potentially result in innovative outcomes [ 82 , 83 ].

Additionally, chatbots, including ChatGPT, have the potential to significantly impact students' thinking abilities, including retention, reasoning, analysis skills [ 19 , 45 ], and foster innovation and creativity capabilities [ 83 ]. This review found that ChatGPT could contribute to improving a wide range of skills among students. However, it found that frequent use of ChatGPT may result in a decrease in innovative capacities, collaborative skills and cognitive capacities, and students' motivation to attend classes, as well as could lead to reduced higher-order thinking skills among students [ 22 , 29 ]. Therefore, immediate action is needed to carefully examine the long-term impact of chatbots such as ChatGPT, on learning outcomes as well as to explore its incorporation into educational settings as a supportive tool without compromising students' cognitive development and critical thinking abilities. In the same vein, the review also found that it is challenging to draw a consistent conclusion regarding the potential of ChatGPT to aid self-directed learning approach. This finding aligns with the recent study of Baskara [ 8 ]. Therefore, further research is needed to explore the potential of ChatGPT for self-directed learning. One potential solution involves utilizing learning analytics as a novel approach to examine various aspects of students' learning and support them in their individual endeavors [ 32 ]. This approach can bridge this gap by facilitating an in-depth analysis of how learners engage with ChatGPT, identifying trends in self-directed learning behavior, and assessing its influence on their outcomes.

Turning to the significant concerns, on the other hand, a fundamental challenge with LLM-based chatbots, including ChatGPT, is the accuracy and quality of the provided information and responses, as they provide false information as truth—a phenomenon often referred to as "hallucination" [ 3 , 49 ]. In this context, this review found that the provided information was not entirely satisfactory. Consequently, the utilization of chatbots presents potential concerns, such as generating and providing inaccurate or misleading information, especially for students who utilize it to support their learning. This finding aligns with other findings [ 6 , 30 , 35 , 40 ] which revealed that incorporating chatbots such as ChatGPT, into education presents challenges related to its accuracy and reliability due to its training on a large corpus of data, which may contain inaccuracies and the way users formulate or ask ChatGPT. Therefore, immediate action is needed to address these potential issues. One possible solution is to equip students with the necessary skills and competencies, which include a background understanding of how to use it effectively and the ability to assess and evaluate the information it generates, as the accuracy and the quality of the provided information depend on the input, its complexity, the topic, and the relevance of its training data [ 28 , 49 , 86 ]. However, it's also essential to examine how learners can be educated about how these models operate, the data used in their training, and how to recognize their limitations, challenges, and issues [ 79 ].

Furthermore, chatbots present a substantial challenge concerning maintaining academic integrity [ 20 , 56 ] and copyright violations [ 83 ], which are significant concerns in education. The review found that the potential misuse of ChatGPT might foster cheating, facilitate plagiarism, and threaten academic integrity. This issue is also affirmed by the research conducted by Basic et al. [ 7 ], who presented evidence that students who utilized ChatGPT in their writing assignments had more plagiarism cases than those who did not. These findings align with the conclusions drawn by Cotton et al. [ 13 ], Hisan and Amri [ 33 ] and Sullivan et al. [ 75 ], who revealed that the integration of chatbots such as ChatGPT into education poses a significant challenge to the preservation of academic integrity. Moreover, chatbots, including ChatGPT, have increased the difficulty in identifying plagiarism [ 47 , 67 , 76 ]. The findings from previous studies [ 1 , 84 ] indicate that AI-generated text often went undetected by plagiarism software, such as Turnitin. However, Turnitin and other similar plagiarism detection tools, such as ZeroGPT, GPTZero, and Copyleaks, have since evolved, incorporating enhanced techniques to detect AI-generated text, despite the possibility of false positives, as noted in different studies that have found these tools still not yet fully ready to accurately and reliably identify AI-generated text [ 10 , 51 ], and new novel detection methods may need to be created and implemented for AI-generated text detection [ 4 ]. This potential issue could lead to another concern, which is the difficulty of accurately evaluating student performance when they utilize chatbots such as ChatGPT assistance in their assignments. Consequently, the most LLM-driven chatbots present a substantial challenge to traditional assessments [ 64 ]. The findings from previous studies indicate the importance of rethinking, improving, and redesigning innovative assessment methods in the era of chatbots [ 14 , 20 , 64 , 75 ]. These methods should prioritize the process of evaluating students' ability to apply knowledge to complex cases and demonstrate comprehension, rather than solely focusing on the final product for assessment. Therefore, immediate action is needed to address these potential issues. One possible solution would be the development of clear guidelines, regulatory policies, and pedagogical guidance. These measures would help regulate the proper and ethical utilization of chatbots, such as ChatGPT, and must be established before their introduction to students [ 35 , 38 , 39 , 41 , 89 ].

In summary, our review has delved into the utilization of ChatGPT, a prominent example of chatbots, in education, addressing the question of how ChatGPT has been utilized in education. However, there remain significant gaps, which necessitate further research to shed light on this area.

7 Conclusions

This systematic review has shed light on the varied initial attempts at incorporating ChatGPT into education by both learners and educators, while also offering insights and considerations that can facilitate its effective and responsible use in future educational contexts. From the analysis of 14 selected studies, the review revealed the dual-edged impact of ChatGPT in educational settings. On the positive side, ChatGPT significantly aided the learning process in various ways. Learners have used it as a virtual intelligent assistant, benefiting from its ability to provide immediate feedback, on-demand answers, and easy access to educational resources. Additionally, it was clear that learners have used it to enhance their writing and language skills, engaging in practices such as generating ideas, composing essays, and performing tasks like summarizing, translating, paraphrasing texts, or checking grammar. Importantly, other learners have utilized it in supporting and facilitating their directed and personalized learning on a broad range of educational topics, assisting in understanding concepts and homework, providing structured learning plans, and clarifying assignments and tasks. Educators, on the other hand, found ChatGPT beneficial for enhancing productivity and efficiency. They used it for creating lesson plans, generating quizzes, providing additional resources, and answers learners' questions, which saved time and allowed for more dynamic and engaging teaching strategies and methodologies.

However, the review also pointed out negative impacts. The results revealed that overuse of ChatGPT could decrease innovative capacities and collaborative learning among learners. Specifically, relying too much on ChatGPT for quick answers can inhibit learners' critical thinking and problem-solving skills. Learners might not engage deeply with the material or consider multiple solutions to a problem. This tendency was particularly evident in group projects, where learners preferred consulting ChatGPT individually for solutions over brainstorming and collaborating with peers, which negatively affected their teamwork abilities. On a broader level, integrating ChatGPT into education has also raised several concerns, including the potential for providing inaccurate or misleading information, issues of inequity in access, challenges related to academic integrity, and the possibility of misusing the technology.

Accordingly, this review emphasizes the urgency of developing clear rules, policies, and regulations to ensure ChatGPT's effective and responsible use in educational settings, alongside other chatbots, by both learners and educators. This requires providing well-structured training to educate them on responsible usage and understanding its limitations, along with offering sufficient background information. Moreover, it highlights the importance of rethinking, improving, and redesigning innovative teaching and assessment methods in the era of ChatGPT. Furthermore, conducting further research and engaging in discussions with policymakers and stakeholders are essential steps to maximize the benefits for both educators and learners and ensure academic integrity.

It is important to acknowledge that this review has certain limitations. Firstly, the limited inclusion of reviewed studies can be attributed to several reasons, including the novelty of the technology, as new technologies often face initial skepticism and cautious adoption; the lack of clear guidelines or best practices for leveraging this technology for educational purposes; and institutional or governmental policies affecting the utilization of this technology in educational contexts. These factors, in turn, have affected the number of studies available for review. Secondly, the utilization of the original version of ChatGPT, based on GPT-3 or GPT-3.5, implies that new studies utilizing the updated version, GPT-4 may lead to different findings. Therefore, conducting follow-up systematic reviews is essential once more empirical studies on ChatGPT are published. Additionally, long-term studies are necessary to thoroughly examine and assess the impact of ChatGPT on various educational practices.

Despite these limitations, this systematic review has highlighted the transformative potential of ChatGPT in education, revealing its diverse utilization by learners and educators alike and summarized the benefits of incorporating it into education, as well as the forefront critical concerns and challenges that must be addressed to facilitate its effective and responsible use in future educational contexts. This review could serve as an insightful resource for practitioners who seek to integrate ChatGPT into education and stimulate further research in the field.

Data availability

The data supporting our findings are available upon request.

Abbreviations

• Artificial intelligence

AI in education

Large language model

Artificial neural networks

Chat Generative Pre-Trained Transformer

Recurrent neural networks

Long short-term memory

Reinforcement learning from human feedback

Natural language processing

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

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The paper is co-funded by the Academy of Finland (Suomen Akatemia) Research Council for Natural Sciences and Engineering for the project Towards precision education: Idiographic learning analytics (TOPEILA), Decision Number 350560.

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YA contributed to the literature search, data analysis, discussion, and conclusion. Additionally, YA contributed to the manuscript’s writing, editing, and finalization. MS contributed to the study’s design, conceptualization, acquisition of funding, project administration, allocation of resources, supervision, validation, literature search, and analysis of results. Furthermore, MS contributed to the manuscript's writing, revising, and approving it in its finalized state. NP contributed to the results, and discussions, and provided supervision. NP also contributed to the writing process, revisions, and the final approval of the manuscript in its finalized state. MT contributed to the study's conceptualization, resource management, supervision, writing, revising the manuscript, and approving it.

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See Table  4

The process of synthesizing the data presented in Table  4 involved identifying the relevant studies through a search process of databases (ERIC, Scopus, Web of Knowledge, Dimensions.ai, and lens.org) using specific keywords "ChatGPT" and "education". Following this, inclusion/exclusion criteria were applied, and data extraction was performed using Creswell's [ 15 ] coding techniques to capture key information and identify common themes across the included studies.

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Albadarin, Y., Saqr, M., Pope, N. et al. A systematic literature review of empirical research on ChatGPT in education. Discov Educ 3 , 60 (2024). https://doi.org/10.1007/s44217-024-00138-2

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Rapid literature review: definition and methodology

Beata smela.

a Assignity, Cracow, Poland

Mondher Toumi

b Public Health Department, Aix-Marseille University, Marseille, France

Karolina Świerk

Clement francois, małgorzata biernikiewicz.

c Studio Slowa, Wroclaw, Poland

Emilie Clay

d Clever-Access, Paris, France

Laurent Boyer

Introduction: A rapid literature review (RLR) is an alternative to systematic literature review (SLR) that can speed up the analysis of newly published data. The objective was to identify and summarize available information regarding different approaches to defining RLR and the methodology applied to the conduct of such reviews.

Methods: The Medline and EMBASE databases, as well as the grey literature, were searched using the set of keywords and their combination related to the targeted and rapid review, as well as design, approach, and methodology. Of the 3,898 records retrieved, 12 articles were included.

Results: Specific definition of RLRs has only been developed in 2021. In terms of methodology, the RLR should be completed within shorter timeframes using simplified procedures in comparison to SLRs, while maintaining a similar level of transparency and minimizing bias. Inherent components of the RLR process should be a clear research question, search protocol, simplified process of study selection, data extraction, and quality assurance.

Conclusions: There is a lack of consensus on the formal definition of the RLR and the best approaches to perform it. The evidence-based supporting methods are evolving, and more work is needed to define the most robust approaches.

Introduction

A systematic literature review (SLR) summarizes the results of all available studies on a specific topic and provides a high level of evidence. Authors of the SLR have to follow an advanced plan that covers defining a priori information regarding the research question, sources they are going to search, inclusion criteria applied to choose studies answering the research question, and information regarding how they are going to summarize findings [ 1 ].

The rigor and transparency of SLRs make them the most reliable form of literature review [ 2 ], providing a comprehensive, objective summary of the evidence for a given topic [ 3 , 4 ]. On the other hand, the SLR process is usually very time-consuming and requires a lot of human resources. Taking into account a high increase of newly published data and a growing need to analyze information in the fastest possible way, rapid literature reviews (RLRs) often replace standard SLRs.

There are several guidelines on the methodology of RLRs [ 5–11 ]; however, only recently, one publication from 2021 attempted to construct a unified definition [ 11 ]. Generally, by RLRs, researchers understand evidence synthesis during which some of the components of the systematic approach are being used to facilitate answering a focused research question; however, scope restrictions and a narrower search strategy help to make the project manageable in a shorter time and to get the key conclusions faster [ 4 ].

The objective of this research was to collect and summarize available information on different approaches to the definition and methodology of RLRs. An RLR has been run to capture publications providing data that fit the project objective.

To find publications reporting information on the methodology of RLRs, searches were run in the Medline and EMBASE databases in November 2022. The following keywords were searched for in titles and abstracts: ‘targeted adj2 review’ OR ‘focused adj2 review’ OR ‘rapid adj2 review’, and ‘methodology’ OR ‘design’ OR ‘scheme’ OR ‘approach’. The grey literature was identified using Google Scholar with keywords including ‘targeted review methodology’ OR ‘focused review methodology’ OR ‘rapid review methodology’. Only publications in English were included, and the date of publication was restricted to year 2016 onward in order to identify the most up-to-date literature. The reference lists of each included article were searched manually to obtain the potentially eligible articles. Titles and abstracts of the retrieved records were first screened to exclude articles that were evidently irrelevant. The full texts of potentially relevant papers were further reviewed to examine their eligibility.

A pre-defined Excel grid was developed to extract the following information related to the methodology of RLR from guidelines:

• Definition,
• Research question and searches,
• Studies selection,
• Data extraction and quality assessment,
• Additional information.

There was no restriction on the study types to be analyzed; any study reporting on the methodology of RLRs could be included: reviews, practice guidelines, commentaries, and expert opinions on RLR relevant to healthcare policymakers or practitioners. The data extraction and evidence summary were conducted by one analyst and further examined by a senior analyst to ensure that relevant information was not omitted. Disagreements were resolved by discussion and consensus.

Studies selection

A total of 3,898 records (3,864 articles from a database search and 34 grey literature from Google Scholar) were retrieved. After removing duplicates, titles and abstracts of 3,813 articles were uploaded and screened. The full texts of 43 articles were analyzed resulting in 12 articles selected for this review, including 7 guidelines [ 5–11 ] on the methodology of RLRs, together with 2 papers summarizing the results of the Delphi consensus on the topic [ 12 , 13 ], and 3 publications analyzing and assessing different approaches to RLRs [ 4 , 14 , 15 ].

Overall, seven guidelines were identified: from the World Health Organization (WHO) [ 5 ], National Collaborating Centre for Methods and Tools (NCCMT) [ 7 ], the UK government [ 8 ], the Oxford Centre for Evidence Based Medicine [ 9 ], the Cochrane group [ 6 , 11 ], and one multi-national review [ 10 ]. Among the papers that did not describe the guidelines, Gordon et al. [ 4 ] proposed 12 tips for conducting a rapid review in the right settings and discussed why these reviews may be more beneficial in some circumstances. The objective of work conducted by Tricco et al. [ 13 ] and Pandor et al. [ 12 ] was to collect and compare perceptions of rapid reviews from stakeholders, including researchers, policymakers, industry, journal editors, and healthcare providers, and to reach a consensus outlining the domains to consider when deciding on approaches for RLRs. Haby et al. [ 14 ] run a rapid review of systematic reviews and primary studies to find out the best way to conduct an RLR in health policy and practice. In Tricco et al. (2022) [ 15 ], JBI position statement for RLRs is presented.

From all the seven identified guidelines information regarding definitions the authors used for RLRs, approach to the PICOS criteria and search strategy development, studies selection, data extractions, quality assessment, and reporting were extracted.

Cochrane Rapid Reviews Methods Group developed methods guidance based on scoping review of the underlying evidence, primary methods studies conducted, as well as surveys sent to Cochrane representative and discussion among those with expertise [ 11 ]. They analyzed over 300 RLRs or RLR method papers and based on the methodology of those studies, constructed a broad definition RLR, one that meets a minimum set of requirements identified in the thematic analysis: ‘ A rapid review is a form of knowledge synthesis that accelerates the process of conducting a traditional systematic review through streamlining or omitting a variety of methods to produce evidence in a resource-efficient manner .’ This interpretation aligns with more than 50% of RLRs identified in this study. The authors additionally provided several other definitions, depending on specific situations or requirements (e.g., when RLR is produced on stakeholder’s request). It was additionally underlined that RLRs should be driven by the need of timely evidence for decision-making purposes [ 11 ].

Rapid reviews vary in their objective, format, and methods used for evidence synthesis. This is a quite new area, and still no agreement on optimal methods can be found [ 5 ]. All of the definitions are highlighting that RLRs are completed within shorter timeframes than SLRs, and also lack of time is one of the main reasons they are conducted. It has been suggested that most rapid reviews are conducted within 12 weeks; however, some of the resources suggest time between a few weeks to no more than 6 months [ 5 , 6 ]. Some of the definitions are highlighting that RLRs follow the SLR process, but certain phases of the process are simplified or omitted to retrieve information in a time-saving way [ 6 , 7 ]. Different mechanisms are used to enhance the timeliness of reviews. They can be used independently or concurrently: increasing the intensity of work by intensifying the efforts of multiple analysts by parallelization of tasks, using review shortcuts whereby one or more systematic review steps may be reduced, automatizing review steps by using new technologies [ 5 ]. The UK government report [ 8 ] referred to two different RLRs: in the form of quick scoping reviews (QSR) or rapid evidence assessments (REA). While being less resource and time-consuming compared to standard SLRs, QSRs and REAs are designed to be similarly transparent and to minimize bias. QSRs can be applied to rather open-ended questions, e.g., ‘what do we know about something’ but both, QSRs and REAs, provide an understanding of the volume and characteristics of evidence on a specific topic, allowing answering questions by maximizing the use of existing data, and providing a clear picture of the adequacy of existing evidence [ 8 ].

Research questions and searches

The guidelines suggest creating a clear research question and search protocol at the beginning of the project. Additionally, to not duplicate RLRs, the Cochrane Rapid Reviews Methods Group encourages all people working on RLRs to consider registering their search protocol with PROSPERO, the international prospective register of reviews; however, so far they are not formally registered in most cases [ 5 , 6 ]. They also recommend involving key stakeholders (review users) to set and refine the review question, criteria, and outcomes, as well as consulting them through the entire process [ 11 ].

Regarding research questions, it is better to structure them in a neutral way rather than focus on a specific direction for the outcome. By doing so, the researcher is in a better position to identify all the relevant evidence [ 7 ]. Authors can add a second, supportive research question when needed [ 8 ]. It is encouraged to limit the number of interventions, comparators and outcomes, to focus on the ones that are most important for decision-making [ 11 ]. Useful could be also reviewing additional materials, e.g., SLRs on the topic, as well as conducting a quick literature search to better understand the topic before starting with RLRs [ 7 ]. In SLRs researchers usually do not need to care a lot about time spent on creating PICOS, they need to make sure that the scope is broad enough, and they cannot use many restrictions. When working on RLRs, a reviewer may spend more or less time defining each of the components of the study question, and the main step is making sure that PICOS addresses the needs of those who requested the rapid review, and at the same time, it is feasible within the required time frame [ 7 ]. Search protocol should contain an outline of how the following review steps are to be carried out, including selected search keywords and a full strategy, a list of data sources, precise inclusion and exclusion criteria, a strategy for data extraction and critical appraisal, and a plan of how the information will be synthesized [ 8 ].

In terms of searches running, in most cases, an exhaustive process will not be feasible. Researchers should make sure that the search is effective and efficient to produce results in a timely manner. Cochrane Rapid Reviews Methods Group recommends involving an information specialist and conducting peer review of at least one search strategy [ 11 ]. According to the rapid review guidebook by McMaster University [ 7 ], it is important that RLRs, especially those that support policy and program decisions, are being fed by the results of a body of literature, rather than single studies, when possible. It would result in more generalizable findings applied at the level of a population and serve more realistic findings for program decisions [ 7 ]. It is important to document the search strategy, together with a record of the date and any date limits of the search, so that it can easily be run again, modified, or updated. Furthermore, the information on the individual databases included in platform services should always be reported, as this depends on organizations’ subscriptions and must be included for transparency and repeatability [ 7 , 8 ]. Good solution for RLRs is narrowing the scope or searching a limited number of databases and other sources [ 7 ]. Often, the authors use the PubMed/MEDLINE, Cochrane Library, and Embase databases. In most reviews, two or more databases are searched, and common limits are language (usually restricted to English), date, study design, and geographical area. Some RLRs include searching of grey literature; however, contact with authors is rather uncommon [ 5 , 8 ]. According to the flexible framework for restricted systematic review published by the University of Oxford, the search should be run in at least one major scientific database such as PubMed, and one other source, e.g., Google Scholar [ 9 ]. Grey literature and unpublished evidence may be particularly needed and important for intervention questions. It is related to the fact that studies that do not report the effects of interventions are less likely to be published [ 8 ]. If there is any type of evidence that will not be considered by the RLRs, e.g., reviews or theoretical and conceptual studies, it should also be stated in the protocol together with justification [ 8 ]. Additionally, authors of a practical guide published by WHO suggest using a staged search to identify existing SLRs at the beginning, and then focusing on studies with other designs [ 5 ]. If a low number of citations have been retrieved, it is acceptable to expand searches, remove some of the limits, and add additional databases and sources [ 7 ].

Searching for RLRs is an iterative process, and revising the approach is usually needed [ 7 ]. Changes should be confirmed with stakeholders and should be tracked and reflected in the final report [ 5 ].

The next step in the rapid review is the selection of studies consisting of two phases: screening of titles and abstracts, and analysis of full texts. Prior to screening initiation, it is recommended to conduct a pilot exercise using the same 30–50 abstracts and 5–10 full-texts for the entire screening team in order to calibrate and test the review form [ 11 ]. In contrast to SLRs, it can be done by one reviewer with or without verification by a second one. If verification is performed, usually the second reviewer checks only a subset of records and compares them. Cochrane Group, in contrast, recommends a stricter approach: at least 20% of references should be double-screened at titles and abstracts stage, and while the rest of the references may be screened by one reviewer, the excluded items need to be re-examined by second reviewer; similar approach is used in full-text screening [ 11 ]. This helps to ensure that bias was reduced and that the PICOS criteria are applied in a relevant way [ 5 , 8 , 9 , 11 ]. During the analysis of titles and abstracts, there is no need to report reasons for exclusion; however, they should be tracked for all excluded full texts [ 7 ].

Data extraction and quality assessment

According to the WHO guide, the most common method for data extraction in RLRs is extraction done by a single reviewer with or without partial verification. The authors point out that a reasonable approach is to use a second reviewer to check a random sample of at least 10% of the extractions for accuracy. Dual performance is more necessary for the extraction of quantitative results than for descriptive study information. In contrast, Cochrane group recommends that second reviewer should check the correctness and completeness of all data [ 11 ]. When possible, extractions should be limited to key characteristics and outcomes of the study. The same approach to data extraction is also suggested for a quality assessment process within rapid reviews [ 5 , 9 , 11 ]. Authors of the guidebook from McMaster University highlight that data extraction should be done ideally by two reviewers independently and consensus on the discrepancies should always be reached [ 7 ]. The final decision on the approach to this important step of review should depend on the available time and should also reflect the complexity of the research question [ 9 ].

For screening, analysis of full texts, extractions, and quality assessments, researchers can use information technologies to support them by making these review steps more efficient [ 5 ].

Before data reporting, a reviewer should prepare a document with key message headings, executive summary, background related to the topic and status of the current knowledge, project question, synthesis of findings, conclusions, and recommendations. According to the McMaster University guidebook, a report should be structured in a 1:2:20 format, that is, one page for key messages, two pages for an executive summary, and a full report of up to 20 pages [ 7 ]. All the limitations of the RLRs should be analyzed, and conclusions should be drawn with caution [ 5 ]. The quality of the accumulated evidence and the strength of recommendations can be assessed using, e.g., the GRADE system [ 5 ]. When working on references quoting, researchers should remember to use a primary source, not secondary references [ 7 ]. It would be worth considering the support of some software tools to automate reporting steps. Additionally, any standardization of the process and the usage of templates can support report development and enhance the transparency of the review [ 5 ].

Ideally, all the review steps should be completed during RLRs; however, often some steps may need skipping or will not be completed as thoroughly as should because of time constraints. It is always crucial to decide which steps may be skipped, and which are the key ones, depending on the project [ 7 ]. Guidelines suggest that it may be helpful to invite researchers with experience in the operations of SLRs to participate in the rapid review development [ 5 , 9 ]. As some of the steps will be completed by one reviewer only, it is important to provide them with relevant training at the beginning of the process, as well as during the review, to minimize the risk of mistakes [ 5 ].

Additional information

Depending on the policy goal and available resources and deadlines, methodology of the RLRs may be modified. Wilson et al. [ 10 ] provided extensive guidelines for performing RLR within days (e.g., to inform urgent internal policy discussions and/or management decisions), weeks (e.g., to inform public debates), or months (e.g., to inform policy development cycles that have a longer timeline, but that cannot wait for a traditional full systematic review). These approaches vary in terms of data synthesis, types of considered evidence and project management considerations.

In shortest timeframes, focused questions and subquestions should be formulated, typically to conduct a policy analysis; the report should consist of tables along with a brief narrative summary. Evidence from SLRs is often considered, as well as key informant interviews may be conducted to identify additional literature and insights about the topic, while primary studies and other types of evidence are not typically feasible due to time restrictions. The review would be best conducted with 1–2 reviewers sharing the work, enabling rapid iterations of the review. As for RLRs with longer timeline (weeks), these may use a mix of policy, systems and political analysis. Structure of the review would be similar to shorter RLRs – tabular with short narrative summary, as the timeline does not allow for comprehensive synthesis of data. Besides SLRs, primary studies and other evidence may be feasible in this timeframe, if obtained using the targeted searches in the most relevant databases. The review team should be larger, and standardized procedures for reviewing of the results and data extraction should be applied. In contrast to previous timeframe, merit review process may be feasible. For both timeframes, brief consultations with small transdisciplinary team should be conducted at the beginning and in the final stage of the review to discuss important matters.

For RLRs spanning several months, more comprehensive methodology may be adapted in terms of data synthesis and types of evidence. However, authors advise that review may be best conducted with a small review team in order to allow for more in-depth interpretation and iteration.

Studies analyzing methodology

There have been two interesting publications summarizing the results of Delphi consensus on the RLR methodology identified and included in this review [ 12 , 13 ].

Tricco et al. [ 13 ] first conducted an international survey and scoping review to collect information on the possible approaches to the running of rapid reviews, based on which, they employed a modified Delphi method that included inputs from 113 stakeholders to explore the most optimized approach. Among the six most frequent rapid review approaches (not all detailed here) being evaluated, the approach that combines inclusion of published literature only, a search of more than one database and limitations by date and language, study selection by one analyst, data extraction, and quality assessment by one analyst and one verifier, was perceived as the most feasible approach (72%, 81/113 responses) with the potentially lowest risk of bias (12%, 12/103). The approach ranked as the first one when considering timelines assumes updating of the search from a previously published review, no additional limits on search, studies selection and data extraction done by one reviewer, and no quality assessment. Finally, based on the publication, the most comprehensive RLRs can be made by moving on with the following rules: searching more than one database and grey literature and using date restriction, and assigning one reviewer working on screening, data extraction, and risk of bias assessment ( Table 1 ). Pandor et al. [ 12 ] introduced a decision tool for SelecTing Approaches for Rapid Reviews (STARR) that were produced through the Delphi consensus of international experts through an iterative and rigorous process. Participants were asked to assess the importance of predefined items in four domains related to the rapid review process: interaction with commissioners, understanding the evidence base, data extraction and synthesis methods, and reporting of rapid review methods. All items assigned to four domains achieved > 70% of consensus, and in that way, the first consensus-driven tool has been created that supports authors of RLRs in planning and deciding on approaches.

Six most frequent approaches to RLRs (adapted from Tricco et al. [ 13 ]).

Haby et al. [ 14 ] run searches of 11 databases and two websites and developed a comprehensive overview of the methodology of RLRs. With five SLRs and one RCT being finally included, they identified the following approaches used in RLRs to make them faster than full SLRs: limiting the number and scope of questions, searching fewer databases, limited searching of grey literature, restrictions on language and date (e.g., English only, most recent publications), updating the existing SLRs, eliminating or limiting hand searches of reference lists, noniterative search strategies, eliminating consultation with experts, limiting dual study selection, data extraction and quality assessment, minimal data synthesis with short concise conclusions or recommendations. All the SLRs included in this review were consistent in stating that no agreed definition of rapid reviews is available, and there is still no final agreement on the best methodological rules to be followed.

Gordon et al. [ 4 ] explained the advantages of performing a focused review and provided 12 tips for its conduction. They define focused reviews as ‘a form of knowledge synthesis in which the components of the systematic process are applied to facilitate the analysis of a focused research question’. The first tip presented by the authors is related to deciding if a focused review is a right solution for the considered project. RLRs will suit emerging topics, approaches, or assessments where early synthesis can support doctors, policymakers, etc., but also can direct future research. The second, third, and fourth tips highlight the importance of running preliminary searches and considering narrowing the results by using reasonable constraints taking into account the local context, problems, efficiency perspectives, and available time. Further tips include creating a team of experienced reviewers working on the RLRs, thinking about the target journal from the beginning of work on the rapid review, registering the search protocol on the PROSPERO registry, and the need for contacting authors of papers when data available in publications are missing or incongruent. The last three tips are related to the choice of evidence synthesis method, using the visual presentation of data, and considering and describing all the limitations of the focused review.

Finally, a new publication by Tricco et al. from 2022, describing JBI position statement [ 15 ] underlined that for the time being, there is no specific tool for critical appraisal of the RLR’s methodological quality. Instead, reviewers may use available tools to assess the risk of bias or quality of SLRs, like ROBIS, the JBI critical appraisal tools, or the assessment of multiple systematic reviews (AMSTAR).

Inconsistency in the definitions and methodologies of RLR

Although RLR was broadly perceived as an approach to quicken the conduct of conventional SLR, there is a lack of consensus on the formal definition of the RLR, so as to the best approaches to perform it. Only in 2021, a study proposing unified definition was published; however, it is important to note that the most accurate definition was only matching slightly over 50% of papers analysed by the authors, which underlines the lack of homogeneity in the field [ 11 ]. The evidence-based supporting methods are evolving, and more evidence is needed to define the most robust approaches [ 5 ].

Diverse terms are used to describe the RLR, including ‘rapid review’, focused systematic review’, ‘quick scoping reviews’, and ‘rapid evidence assessments’. Although the general principles of conducting RLR are to accelerate the whole process, complexity was seen in the methodologies used for RLRs, as reflected in this study. Also, inconsistencies related to the scope of the questions, search strategies, inclusion criteria, study screening, full-text review, quality assessment, and evidence presentation were implied. All these factors may hamper decision-making about optimal methodologies for conducting rapid reviews, and as a result, the efficiency of RLR might be decreased. Additionally, researchers may tend to report the methodology of their reviews without a sufficient level of detail, making it difficult to appraise the quality and robustness of their work.

Advantages and weaknesses of RLR

Although RLR used simplified approaches for evidence synthesis compared with SLR, the methodologies for RLR should be replicable, rigorous, and transparent to the greatest extent [ 16 ]. When time and resources are limited, RLR could be a practical and efficient tool to provide the summary of evidence that is critical for making rapid clinical or policy-related decisions [ 5 ]. Focusing on specific questions that are of controversy or special interest could be powerful in reaffirming whether the existing recommendation statements are still appropriate [ 17 ].

The weakness of RLR should also be borne in mind, and the trade-off of using RLR should be carefully considered regarding the thoroughness of the search, breadth of a research question, and depth of analysis [ 18 ]. If allowed, SLR is preferred over RLR considering that some relevant studies might be omitted with narrowed search strategies and simplified screening process [ 14 ]. Additionally, omitting the quality assessment of included studies could result in an increased risk of bias, making the comprehensiveness of RLR compromised [ 13 ]. Furthermore, in situations that require high accuracy, for example, where a small relative difference in an intervention has great impacts, for the purpose of drafting clinical guidelines, or making licensing decisions, a comprehensive SLR may remain the priority [ 19 ]. Therefore, clear communications with policymakers are recommended to reach an agreement on whether an RLR is justified and whether the methodologies of RLR are acceptable to address the unanswered questions [ 18 ].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Doula Care: A Review of Outcomes and Impact on Birth Experience

Affiliations.

• 1 Student, Duke University School of Medicine, Duke University.
• 2 Full Circle Trained Doula, Breastfeeding Peer Counselor, NC Community Based Doula Accreditation Board, Licensed Doula, Mobilizing African American Mothers through Empowerment (MAAME), Inc, Durham.
• 3 NC Community Based Doula Accreditation Board, Licensed Doula, Momma's Village-Fayetteville, Inc, Fayetteville, NC.
• 4 Licensed Doula, Sistas Caring 4 Sistas: Community Based Doulas for Social Justice, Asheville, NC.
• 5 Licensed Doula, Mobilizing African American Mothers through Empowerment (MAAME), Inc.
• 6 Assistant Professor of Obstetrics and Gynecology, Division of Maternal Fetal Medicine, Duke University, Durham, NC.
• PMID: 36786720
• DOI: 10.1097/OGX.0000000000001103

Importance: Doulas are trained professionals that provide comprehensive support during the perinatal period. Doula-supported care is associated with improved maternal and infant outcomes including decreased preterm birth, increased breastfeeding initiation, and higher patient satisfaction. In addition, research suggests that doula support is a promising strategy to mitigate racial disparities in maternal and infant health outcomes.

Objective: This article reviews doulas' scope of practice, perinatal outcomes associated with doula-assisted care, and their impact on alleviating racial disparities in maternal-infant outcomes.

Evidence acquisition: A literature search using the search engine PubMed was done. The search terms included ([Doula OR doulas OR labor coach] AND [Preterm OR prenatal care OR race OR racial OR racism OR Black OR African American]). Studies had to be written in English.

Results: The search resulted 90 articles of which 18 original articles and 16 review articles were reviewed. The literature demonstrates that doula support increases vaginal delivery while decreasing preterm birth and low birth weight. Studies also show that doula support is uniquely effective for Black patients and is a promising strategy to reduce health care inequities.

Conclusions and relevance: Doulas may provide significant perinatal benefit for birthing patients and their infants, with advantages also noted for Black patients. The current article provides an overview of the literature focused on doula support.

Publication types

• Infant, Newborn
• Labor, Obstetric*
• Parturition
• Premature Birth*
• Prenatal Care