The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
How ChatGPT impacts student engagement from a systematic review and meta-analysis study
Open accessAbstract
Generative artificial intelligence, such as ChatGPT, has been increasingly integrated into education to change student learning experience. Current empirical studies have mixed results on how ChatGPT impacts student behavioral, cognitive, and emotional engagement. This systematic literature review and meta-analysis explores whether and how ChatGPT impacts student behavioral, cognitive, and emotional engagement. We used the PRISMA method to select, analyze, and report the results. We screened 766 articles from four databases and identified 17 empirical studies with 1735 students for analysis. We compared the effect on student engagement between ChatGPT-based and non-ChatGPT learning. We found a medium effect size on overall student engagement in ChatGPT-based learning in the random effects model. Our analyses further suggest that ChatGPT-based learning is more effective in fostering student behavioral (medium effective size), cognitive (large effective size), and emotional engagement (medium effective size) than non-ChatGPT learning. Our findings revealed ChatGPT is an effective tool for engaging students in learning. We also suggested three roles ChatGPT plays in fostering student engagement: personalized tutoring, programming and technical assistance, and content generation and collaboration. Our systematic literature review revealed potential risks and results in student disengagement, such as over-reliance.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
Learner engagement-cognitive, emotional, and behavioral-plays a critical role in the successful use of AI tools.
“Learner engagement-cognitive, emotional, and behavioral-plays a critical role in the successful use of AI tools (Heung & Chiu, 2025 ).”
From Socratic Mind: Impact of a Novel GenAI-Powered Formative Assessment Tool on Student Learning and Higher-Order Thinking (2026) · cites this paper as Heung & Chiu, 2025
Citations
Cites
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., et al. (2018) · Annals of Internal Medicine · doi:10.7326/m18-0850 · Cited by 43,565
School Engagement: Potential of the Concept, State of the Evidence
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004) · Review of Educational Research · doi:10.3102/00346543074001059 · Cited by 12,581
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326
Using Effect Size—or Why the P Value Is Not Enough
Sullivan, G. M., & Feinn, R. (2012) · Journal of Graduate Medical Education · doi:10.4300/jgme-d-12-00156.1 · Cited by 5,553
Bai, S., Hew, K. F., & Huang, B. (2020) · Educational Research Review · doi:10.1016/j.edurev.2020.100322 · Cited by 994
Chiu, T. K. F. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2023.2253861 · Cited by 852
Self-citationChiu, T. K. F. (2022) · Journal of Research on Technology in Education · doi:10.1080/15391523.2021.1891998 · Cited by 834
Self-citationEffect Size Guidelines, Sample Size Calculations, and Statistical Power in Gerontology
Brydges, C. R. (2019) · Innovation in Aging · doi:10.1093/geroni/igz036 · Cited by 826
AI-generated feedback on writing: insights into efficacy and ENL student preference
Escalante, J., Pack, A., & Barrett, A. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00425-2 · Cited by 589
Unlocking the opportunities through ChatGPT Tool towards ameliorating the education system
Javaid, M., Haleem, A., Singh, R. P., Khan, S., & Khan, I. H. (2023) · BenchCouncil Transactions on Benchmarks, Standards and Evaluations · doi:10.1016/j.tbench.2023.100115 · Cited by 535
Axelson, R. D., & Flick, A. (2010) · Change: The Magazine of Higher Learning · doi:10.1080/00091383.2011.533096 · Cited by 534
Digital support for student engagement in blended learning based on self-determination theory
Chiu, T. K. F. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106909 · Cited by 395
Self-citationDeng, X., & Yu, Z. (2023) · Sustainability · doi:10.3390/su15042940 · Cited by 298
Chiu, T. K. F. (2024) · Educational technology research and development · doi:10.1007/s11423-024-10366-w · Cited by 235
Self-citationPellas, N. (2023) · Education Sciences · doi:10.3390/educsci13111155 · Cited by 95
Facilitating nursing and health education by incorporating ChatGPT into learning designs
Chang (2024) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.30191/ets.202401_27(1).tp02 · Cited by 61
Flagged first, then by citations
Research works printed but not linked: 34
- Al Shloul, 2024, Role of activity-based learning and ChatGPT on students' performance in education, Computers and Education: Artificial Intelligence, 6
- Alneyadi, 2023, ChatGPT: Revolutionizing student achievement in the electronic magnetism unit for eleventh-grade students in Emirates schools, Contemporary Educational Technology, 15, 448, 10.30935/cedtech/13417 · DOI · Paper page
- Bakker, 2015, Student engagement and performance: A weekly diary study on the role of openness, Motivation and Emotion, 39, 49, 10.1007/s11031-014-9422-5 · DOI
- Benavides-Varela, 2020, Effectiveness of digital-based interventions for children with mathematical learning difficulties: A meta-analysis, Computers & Education, 157, 10.1016/j.compedu.2020.103953 · DOI
- Bilal Khallel, 2024, Examining students' self-regulation skills, confidence to learn online, and perception of satisfaction and usefulness of online classes in three suggested online learning environments that integrates ChatGPT, Online learning (Newburyport, Mass.), 28
- Boghossian, 2006, Behaviorism, constructivism, and socratic pedagogy, Educational Philosophy and Theory, 38, 10.1111/j.1469-5812.2006.00226.x · DOI
- Chiu, 2024, Teacher support and student motivation to learn with artificial intelligence (AI) chatbot, Interactive Learning Environments, 32, 3240
- Christenson, 2012, Handbook of research on student engagement [doi:10.1007/978-1-4614-2018-7], Springer Science + Business Media · DOI · Paper page
- Dindorf, 2024, Exploring decision-making competence in sugar-substitute choices: A cross-disciplinary investigation among chemistry and sports and health students, Education Sciences, 14, 531, 10.3390/educsci14050531 · DOI
- Fryer, 2019, Chatbot learning partners: Connecting learning experiences, interest and competence, Computers in Human Behavior, 93, 279, 10.1016/j.chb.2018.12.023 · DOI · Paper page
- Huesca, 2024, Effectiveness of using ChatGPT as a tool to strengthen benefits of the flipped learning strategy, Education Sciences, 14, 660, 10.3390/educsci14060660 · DOI
- Jing, 2024, What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study, Humanities & social sciences communications, 11, 319, 10.1057/s41599-024-02751-w · DOI
- Kahu, 2013, Framing student engagement in higher education, Studies in Higher Education, 38, 758, 10.1080/03075079.2011.598505 · DOI · Paper page
- Kerr, 2016, Adaptive learning, ELT Journal, 70, 88, 10.1093/elt/ccv055 · DOI
- Kosar, 2024, Computer science education in ChatGPT era: Experiences from an experiment in a programming course for novice programmers, Mathematics, 12, 629, 10.3390/math12050629 · DOI
- Li, 2024, Systematics review on artificial intelligence chatbots and ChatGPT for language learning and research from self-determination theory (SDT): What are the roles of teachers?, Interactive Learning Environments, 1
- Ng, 2024, Empowering student self-regulated learning and science education through ChatGPT: A pioneering pilot study, British Journal of Educational Technology, 55, 1328, 10.1111/bjet.13454 · DOI
- Qureshi, 2023, Exploring the use of ChatGPT as a tool for learning and assessment in undergraduate computer science curriculum: Opportunities and challenges, arXiv.org
- Reed, 2008, Predictive validity evidence for medical education research study quality instrument scores: Quality of submissions to JGIM's medical education special issue, Journal of General Internal Medicine, 23, 903, 10.1007/s11606-008-0664-3 · DOI
- Reeve, 2013, How students create motivationally supportive learning environments for themselves: The concept of agentic engagement, Journal of Educational Psychology, 105, 579, 10.1037/a0032690 · DOI · Paper page
- Saritepeci, 2024, Effectiveness of artificial intelligence integration in design-based learning on design thinking mindset, creative and reflective thinking skills: An experimental study, Education and Information Technologies, 10.1007/s10639-024-12829-2 · DOI
- Sinatra, 2015, The challenges of defining and measuring student engagement in science, Educational Psychologist, 50, 1, 10.1080/00461520.2014.1002924 · DOI · Paper page
- Sun, 2024, Would ChatGPT-facilitated programming mode impact college students' programming behaviors, performances, and perceptions? An empirical study, International Journal of Educational Technology in Higher Education, 21, 14, 10.1186/s41239-024-00446-5 · DOI · Paper page
- Turner, 2013, Publication bias, with a focus on psychiatry: Causes and solutions, CNS Drugs, 27, 457, 10.1007/s40263-013-0067-9 · DOI
- Wardat, 2024, Integrating ChatGPT in grade 12 Quantum theory education: An exploratory study at emirate school (UAE), International Journal of Information and Education Technology, 14, 389, 10.18178/ijiet.2024.14.3.2061 · DOI
- Weng, 2023, Competency development of pre-service teachers during video-based learning: A systematic literature review and meta-analysis, Computers and education, 199, 10.1016/j.compedu.2023.104790 · DOI
- Wu, 2024, Promoting self-regulation progress and knowledge construction in blended learning via ChatGPT-based learning aid, Journal of Educational Computing Research, 61, 3, 10.1177/07356331231191125 · DOI
- Yildiz Durak, 2023, Conversational agent-based guidance: Examining the effect of chatbot usage frequency and satisfaction on visual design self-efficacy, engagement, satisfaction, and learner autonomy, Education and Information Technologies, 28, 471, 10.1007/s10639-022-11149-7 · DOI
- Yilmaz, 2023, The effect of generative artificial intelligence (AI)-based tool use on students' computational thinking skills, programming self-efficacy and motivation, Computers and Education: Artificial Intelligence, 4
- Yin, 2021, Conversation technology with micro-learning: The impact of chatbot-based learning on students' learning motivation and performance, Journal of Educational Computing Research, 59, 10.1177/0735633120952067 · DOI · Paper page
- Zhan, 2022, The effectiveness of gamification in programming education: Evidence from a meta-analysis, Computers and Education: Artificial Intelligence, 3
- Zhao, 2023, The impact of the use of ChatGPT in enhancing students' engagement and learning outcomes in higher education: A review, International Journal of Academic Research in Business and Social Sciences, 13, 10.6007/IJARBSS/v13-i12/20258 · DOI
- Zimmerman, 2000, Chapter 2-attaining self-regulation: A social cognitive perspective, 13
- Zimmerman, 2008, Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects, American Educational Research Journal, 45, 166, 10.3102/0002831207312909 · DOI · Paper page
Cited by
Sorted by citations
Wang, J., & Fan, W. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04787-y · Cited by 322
RetractedXia, Q., Li, W., Yang, Y., Weng, X., & Chiu, T. K. F. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100455 · Cited by 45
Self-citationThe Impact of ChatGPT on Students' Academic Achievement: A Meta‐Analysis
Liu, Z., Zuo, H., & Lu, Y. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70096 · Cited by 44
Zhao, Y., Yue, Y., Sun, Z., Jiang, Q., & Li, G. (2025) · Journal of Intelligence · doi:10.3390/jintelligence13120160 · Cited by 37
Vendrell, M., & Johnston, S.-K. (2026) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2026.100572 · Cited by 43
ChatGPT as a cognitive crutch: Evidence from a randomized controlled trial on knowledge retention
Barcaui, A. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.102287 · Cited by 51
Lee, J., Hung, J.-T., Yilmaz Soylu, M., Popescu, D., Cui, C. Z., Grigoryan, G., Joyner, D. A., & Harmon, S. W. (2026) · Technology, Knowledge and Learning · doi:10.1007/s10758-026-10007-6 · Cited by 23
Wu, M., & Ouyang, F. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10211-x
Metadata
- Authors
- Heung, Y. M. E., & Chiu, T. K. F.
- Affiliations
- Chinese University of Hong Kong (HK)
- Corresponding author
- Chiu, Thomas K.F.
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2025-06
- Volume
- 8
- Pages
- 100361
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4406071412
- Cited by
- 229
- References
- 17
- Citations by year
- 2026: 149 · 2025: 80
- FWCI
- 24.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (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, student engagement, behavioral engagement, cognitive engagement, emotional engagement, personalized tutoring, overreliance on AI, student disengagement, content creation, collaboration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review