Cited by 191Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationIntelligent Tutoring Systems and Adaptive Learning

The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index; none of the 84 sources its claims cite is checked for support yet.

A systematic literature review of empirical research on ChatGPT in education

Open access

Abstract

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.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This systematic review synthesizes 14 empirical studies published in 2022 and up to 10 April 2023 on how students and teachers initially used ChatGPT in education, finding it served as a virtual assistant, writing aid, and teaching productivity tool, while raising concerns about accuracy, academic integrity, and overuse harming collaboration and innovation. The authors call for structured training, clear guidelines, and redesigned assessment.

Key findings

  • Learners used ChatGPT as a virtual intelligent assistant (9 studies) for on-demand answers, immediate feedback, and learning resources; as a writing and language proficiency assistant (6 studies) for generating ideas, composing essays, summarizing, translating, paraphrasing, and grammar checking; as a resource for self-directed and personalized learning (5 studies); and as a tool for enhancing competencies and academic success (6 and 7 studies respectively).
  • Teachers used ChatGPT to create lesson plans, generate quizzes, and provide additional resources, enhancing productivity and efficiency and enabling new teaching methodologies (5 studies).
  • Negative effects: results of specific studies (n = 3, 21.4%) show overuse of ChatGPT may negatively impact innovative capacities and collaborative learning competencies among learners; one study [S5] reported students suggesting it may harm collaborative learning.
  • Most reviewed studies recommend structured training, support, and clear guidelines for learners and educators, including critical evaluation skills and strategies for integrating human interaction into AI-mediated learning.

Methods

  • Systematic literature review following PRISMA 2020 and Okoli's (2015) steps, with quality appraisal using Fink's standards (two articles excluded for insufficient methodological detail).
  • Search of Dimensions.ai, Scopus, Web of Science, ERIC, and Lens.org using ("ChatGPT" AND "Education"), conducted 3–10 April 2023, yielding 276 articles; after duplicate removal 135 unique articles, then 26 after inclusion/exclusion screening, and 14 eligible for analysis after excluding studies solely testing ChatGPT capabilities.
  • Data extraction and interpretation used Creswell's (2015) open, axial, and selective coding techniques; extracted data covered authors, titles, years, educational levels, methodologies, sample sizes, participants, aims, data sources, and analysis methods.

Limitations

  • Stated: the limited number of reviewed studies, attributed to the novelty of the technology, lack of clear guidelines or best practices, and institutional or governmental policies affecting its educational use.
  • Stated: the review covers the original ChatGPT based on GPT-3 or GPT-3.5, so studies using GPT-4 may yield different findings; follow-up systematic reviews and long-term studies are needed.
  • Evident from the text: the search window closed on 10 April 2023, only months after ChatGPT's November 2022 launch; nine of the reviewed studies had samples of fewer than 50 participants, and most were conducted in higher education institutions (11 of 14), limiting generalizability.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s44217-024-00138-2

Cites

86 of 86 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 84 cited sources checked · 0 supported · 0 flagged

Show all 57 claims

  • It may state two separate claims as one. 66
  • Probably not a substantial claim. 36
89 of 89
  • The paper relies on this without support.

    The existing literature lacks a systematic literature review of empirical studies.

    “However, the existing literature lacks a systematic literature review of empirical studies.”
  • The paper relies on this without support.

    ChatGPT is widely adopted 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.

    “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.”
  • The paper relies on this without support.

    The 14 selected studies are representative of empirical research on ChatGPT in education, so that the review's synthesized conclusions can be generalized to ChatGPT in education.

    “From the analysis of 14 selected studies, the review revealed the dual-edged impact of ChatGPT in educational settings.”
  • The paper relies on this without support.

    The findings reported by the reviewed studies are valid and reliable enough to be synthesized into review-level conclusions.

    “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 paper relies on this without support.

    New technologies often face initial skepticism and cautious adoption.

    “as new technologies often face initial skepticism and cautious adoption”
  • The paper relies on this without support.

    There is a lack of clear guidelines or best practices for leveraging ChatGPT for educational purposes.

    “the lack of clear guidelines or best practices for leveraging this technology for educational purposes”
  • The paper relies on this without support.

    Institutional or governmental policies affect the utilization of ChatGPT in educational contexts.

    “institutional or governmental policies affecting the utilization of this technology in educational contexts”
  • The paper relies on this without support.

    The original version of ChatGPT is based on GPT-3 or GPT-3.5.

    “the utilization of the original version of ChatGPT, based on GPT-3 or GPT-3.5”
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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Journalism and construction findings cite studies assigned to different fields

    Minor

    The competencies section labels S5 as journalism and S9 as construction education. The field breakdown instead assigns S5 to mathematics, S9 to journalism, and S3 to construction education.

  • A student-writing finding cites a teacher-only study

    Minor

    The writing section attributes a finding about students' mastery to S11, whereas the population section says S11 specifically targeted elementary school teachers.

  • S6 appears in two separate study-population categories

    Minor

    S6 is listed both among studies involving university students and among those focused on university teachers, rather than in the category for studies including both.

  • S4 is classified as qualitative despite a reported mixed-methods design

    Minor

    The methodology classification places S4 among qualitative studies, while the sample-size discussion explicitly calls it a mixed-methods study with qualitative and quantitative analyses.

  • S4 also had more than 100 participants in one analysis

    Minor

    The text says S7 was the only study with more than 100 participants, but it reports 110 participants for S4's quantitative analysis alone.

  • The list of small-sample studies contains eight, not nine

    Minor

    The four individually named studies plus S10 through S13 make eight studies, although the text says nine.

  • S12 and S14 have both unspecified and university-level populations

    Minor

    The educational-level section says S12 and S14 did not specify their populations' educational level, but the population section identifies both as including university teachers and students.

7 of 7

Citations

Cites

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Show all 81 references

Research works printed but not linked: 7

  1. Ausat AMA, Massang B, Efendi M, Nofirman N, Riady Y. Can chat GPT replace the role of the teacher in the classroom: a fundamental analysis. J Educ. 2023;5(4):16100–6.
  2. Creswell JW. Educational research: planning, conducting, and evaluating quantitative and qualitative research [Ebook]. 4th ed. London: Pearson Education; 2015.
  3. Hirsto L, Saqr M, López-Pernas S, Valtonen T. (2022). A systematic narrative review of learning analytics research in K-12 and schools. Proceedings. https://ceur-ws.org/Vol-3383/FLAIEC22_paper_9536.pdf
  4. Limna P. A Review of Artificial Intelligence (AI) in Education during the Digital Era. 2022. https://ssrn.com/abstract=4160798
  5. Saqr M, Matcha W, Uzir N, Jovanović J, Gašević D, López-Pernas S. Transferring effective learning strategies across learning contexts matters: a study in problem-based learning. Australas J Educ Technol. 2023;39(3):9.
  6. Szabo A. ChatGPT is a breakthrough in science and education but fails a test in sports and exercise psychology. Balt J Sport Health Sci. 2023;1(128):25–40. https://doi.org/10.33607/bjshs.v127i4.1233. · DOI
  7. Tedre M, Kahila J, Vartiainen H. (2023). Exploration on how co-designing with AI facilitates critical evaluation of ethics of AI in craft education. In: Langran E, Christensen P, Sanson J (Eds). Proceedings of Society for Information Technology and Teacher Education International Conference. 2023. pp. 2289–2296.

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Metadata

Authors
Albadarin, Y., Saqr, M., Pope, N., & Tukiainen, M.
Affiliations
University of Eastern Finland (FI)
Corresponding author
Albadarin, Yazid
Venue
Discover Education
Published
2024-05-26
Volume
3
Issue
1
ISSN
2731-5525 (ISSN-L)
OpenAlex
W4399028114
Cited by
191
References
81
Citations by year
2026: 98 · 2025: 73 · 2024: 19
FWCI
11.30
Type
journal article
Language
en
Open access
Locations
  • Discover Education (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
ChatGPT, generative AI in education, artificial intelligence in education, student use of AI, teacher use of AI, personalized learning, cooperative learning, critical evaluation skills, responsible AI use, overreliance on AI, lesson planning, human-AI collaboration, AI policy in education

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