The DOI matches its Crossref record; 107 of the 108 references it cites were found in a registry or an index.
The influence of ChatGPT on student engagement: A systematic review and future research agenda
Open accessAbstract
ChatGPT, a state-of-the-art artificial intelligence (AI) chatbot, has gained considerable attention as a transformative yet controversial tool for enhancing teaching and learning experiences. Several reviews and numerous articles have been written about harnessing ChatGPT in education since its release on November 30, 2022. Besides summarising its strengths, weaknesses, opportunities, and threats (SWOT) as identified in previous systematic reviews of ChatGPT research, this systematic review aims to develop a new understanding of its influence on student engagement by synthesising the existing related research using a three-dimensional framework comprising behavioural, emotional, and cognitive aspects. We searched relevant databases and included 72 empirical studies published within one year of ChatGPT's initial release. The findings reveal robust but narrowly focused evidence related to behavioural engagement (i.e., work with ChatGPT) and disengagement (i.e., academic dishonesty). The evidence related to the emotional aspect is mixed, with instances of both engagement (e.g., satisfaction and interest/fun) and disengagement (e.g., disappointment and worry/anxiety). There is broad but weak evidence regarding cognitive engagement (e.g., increased understanding and positive self-perception) and disengagement (e.g., reduced critical thinking and overreliance). Our review uncovers several under-explored indicators of student engagement, pointing to the need for further research. Specifically, future studies could focus on students' study habits and attendance (behavioural engagement), social interaction (emotional engagement), and self-regulation and critical thinking (cognitive engagement) in ChatGPT-supported learning environments.
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“This spike likely correlates with the widespread release and adoption of generative AI tools, such as ChatGPT, which induced academic interest and application development [40,41].”
From Systematic review of artificial intelligence in education: trends, benefits, and challenges (2025) · cites this paper as [40]
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“This aligns with recent literature indicating a surge in generative AI adoption in education due to its versatility in producing personalized content and feedback [40,41].”
From Systematic review of artificial intelligence in education: trends, benefits, and challenges (2025) · cites this paper as [40]
Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
(2001) · Cited by 25,534
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
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
Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research
F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014) · European Business Review · doi:10.1108/ebr-10-2013-0128 · Cited by 11,728
Becoming a Self-Regulated Learner: An Overview
Zimmerman, B. J. (2002) · Theory Into Practice · doi:10.1207/s15430421tip4102_2 · Cited by 10,197
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126
Handbook of Research on Student Engagement
(2012) · doi:10.1007/978-1-4614-2018-7 · Cited by 3,050
Reconsidering Research on Learning from Media
Clark, R. E. (1983) · Review of Educational Research · doi:10.3102/00346543053004445 · Cited by 2,715
Parental Involvement and Students' Academic Achievement: A Meta-Analysis
Fan, X., & Chen, M. (2001) · Educational Psychology Review · doi:10.1023/a:1009048817385 · Cited by 2,648
Flagged first, then by citations
1 of the 108 references couldn’t be matched to a known paper.
Research works printed but not linked: 7
- Alqasham, 2023, ChatGPT in the Saudi EFL classroom: A study of learner usage patterns and possibilities in learning optimization, Migration Letters, 20, 1251
- Bašić, 2023, ChatGPT-3.5 as writing assistance in students' essays, Humanities and Social Sciences Communications, 10, 750, 10.1057/s41599-023-02269-7 · DOI · Paper page
- Javier, 2023, Developing secondary school English language learners' productive and critical use of ChatGPT, TESOL Journal
- Limo, 2023, Personalized tutoring: ChatGPT as a virtual tutor for personalized learning experiences, Social Space, 23, 293
- Muñoz, 2023, Examining the impacts of ChatGPT on student motivation and engagement, Social Space, 23, 1
- 2022, Introducing ChatGPT
- Zhang, 2023, A systematic review of ChatGPT use in K-12 education, European Journal of Education
Cited by
Sorted by citations
Items 201–300 of 397
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Tracing student engagement in dialogues with GenAI in assessment: A semester-long exploratory study
Luo, J. J., & Yin, X. (2026) · Innovations in Education and Teaching International · doi:10.1080/14703297.2026.2663354 · Cited by 3
Albadry, H., & Asiri, S. (2026) · Learning Research and Practice · doi:10.1080/23735082.2026.2660729 · Cited by 2
Song, Z., Lai, C., Huang, X., & Lin, C. (2026) · Computers & Education · doi:10.1016/j.compedu.2026.105654 · Cited by 3
ZHANG, Z., & Liu, T. (2026) · International Journal of Applied Linguistics · doi:10.1111/ijal.70217 · Cited by 2
Bai, Y.-Q. (2026) · Learning and Instruction · doi:10.1016/j.learninstruc.2026.102390 · Cited by 2
Du, J. L., & Chen, Y. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2026.1802007 · Cited by 4
Yao, Y., Rong, M., Chen, X., & Zhu, X. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2683868 · Cited by 2
Wu, Y., Lu, X. Y., & Chenghua, L. (2026) · The International Journal of Management Education · doi:10.1016/j.ijme.2026.101485 · Cited by 2
Lo, C. K., Huang, X., Xu, S., Ko, L. W., Cheung, H. Y. A., Pang, W. F., Ho, T. K., Lam, Y. P., Poon, M. L., & Mo, C. H. (2024) · International Workshop on Artificial Intelligence and Education (WAIE) · doi:10.1109/waie63876.2024.00008 · Cited by 2
Self-citationBessas, N., Tzanaki, E., Vavougios, D., & Plagianakos, V. P. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101610 · Cited by 4
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Ocak, C., Hodges, C. B., & Akcaoğlu, M. (2025) · Signals and communication technology · doi:10.1007/978-3-031-96855-6_10 · Cited by 3
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Adeeb, E., & Müldner, K. (2025) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3702652.3744207 · Cited by 1
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Wang, Q., & Yao, N. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13816-x · Cited by 1
Lin, Y.-R., & Jiao, X. (2025) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2025.102044 · Cited by 3
Chen, Y., Wu, X., Zhong, Y., & Huang, C. (2025) · Communications in computer and information science · doi:10.1007/978-981-95-4499-8_31 · Cited by 1
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Ocak, C., Kopcha, T. J., Hodges, C. B., Sadık, O., & Özoğul, G. (2025) · TechTrends · doi:10.1007/s11528-025-01149-y · Cited by 1
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Gül, F. Ö. (2025) · Journal of Educational Technology and Online Learning · doi:10.31681/jetol.1781815 · Cited by 1
Alqurashi, N., & Hamed, D. M. (2026) · SAGE Open · doi:10.1177/21582440261419890 · Cited by 1
Chen, X., Liu, J., Liu, Y., Xiang, H., Guo, X., Cai, X., & Wang, X. (2026) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2026.102166 · Cited by 3
Lin, Y., & Hung, C. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-13921-5 · Cited by 2
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Yuan, R. E., Wang, K., Wang, Z., & He, W. (2026) · Educational Research Review · doi:10.1016/j.edurev.2026.100787 · Cited by 6
Xu, Z. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14013-0 · Cited by 1
Manganello, F., Masi, G., Nico, A., & Boccuzzi, G. (2026) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2026.1787728 · Cited by 1
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Chou, C.-M., Shen, T.-C., & Shen, T.-C. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2668022 · Cited by 2
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Tokarchuk, Y. A., Rubtsova, O. V., & Tokarchuk, A. M. (2026) · Journal of Modern Foreign Psychology · doi:10.17759/jmfp.2026150201 · Cited by 1
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Dahake, P. S., Dahake, N. S., & Santos, V. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5097-4.ch018
Ozcan, S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5384926
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Schmidt, L., Obergassel, N., & Roelle, J. (2025) · Applied Cognitive Psychology · doi:10.1002/acp.70148
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Tärning, B., Tjøstheim, T. A., & Wallin, A. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1653992 · Cited by 2
Lo, C. K., Xu, S., Yip, C. F., & Chen, G. (2025) · Lecture notes in educational technology · doi:10.1007/978-981-95-0405-3_19
Self-citationHeinbach, C. (2025) · Informatik-Spektrum · doi:10.1007/s00287-025-01600-7
Kim, B.-S., & Kim, S.-H. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2605186
Understanding GenAI Adoption in Education: A Systematic Literature Review
Hidayat, A. A., Rospricilia, T. A., Rosidah, N. A., Fauzia, R. V., & Putra, I. M. (2025) · Journal of Multimedia Trend and Technology. · doi:10.35671/jmtt.v4i2.139 · Cited by 1
A systematic review of engagement in medical education (Preprint)Preprint
Lee, J. W. Y., Balaji, A., & Bello, F. (2026) · doi:10.2196/preprints.92372
Lo, C. K., Huang, X., Yee, T. L., Bai, S., Singh, M., Zhang, Q., Cheung, H. W., & Ko, L. W. (2025) · International Workshop on Artificial Intelligence and Education (WAIE) · doi:10.1109/waie67422.2025.11381152
Self-citationSaeli, H., Mahmoodi‐Bakhtiari, B., & Ringer, J. M. (2026) · Iranian and Persian Studies. · doi:10.1007/978-981-95-1046-7_8
Aldous, K. K., Salminen, J. O., Jung, S.-G., Azem, J. Y., Medina, J., Khan, S. M., Alabed, A., & Jansen, B. J. (2025) · International Conference on Foundation and Large Language Models (FLLM) · doi:10.1109/fllm67465.2025.11390874
Yin, T., & Xu, L. (2025) · New frontiers in translation studies · doi:10.1007/978-981-95-4798-2_10
Kong, B., & Maruthai, E. (2026) · BMC Psychology · doi:10.1186/s40359-026-04330-x
Ovando-Bravo, L. P., Cuenca, G. K. C., Ulloa, N. V. C., & Vera, G. J. T. (2026) · Horizon Nexus Journal. · doi:10.70881/hnj/v4/n1/117 · Cited by 1
Yao, Y., Tu, X., Liu, C., & Liu, Y. (2026) · International Conference on Artificial Intelligence and Social Network Systems (AISNS) · doi:10.1109/aisns67921.2026.11440580
Lo, C. K., Yeung, L. C., Huang, X., Xu, S., Song, Y., & Chen, G. (2026) · Lecture notes in educational technology · doi:10.1007/978-981-95-8824-4_15
Self-citationWang, J., Ren, J., Liu, W., Rong, Z., Shi, Z., Zhao, Y. W., Zou, S., & Gao, S. (2026) · Journal of Science Education and Technology · doi:10.1007/s10956-026-10311-x
Sang, H. T., & Loi, N. V. (2026) · Studies in computational intelligence · doi:10.1007/978-3-032-18392-7_7 · Cited by 1
Awashreh, R. A., Ghunaimi, H. A., & Ghenaimi, S. A. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.102788
Kaplar, M., Kaplar, S., Vucic, M., Ivanović, L., Stevanović, A., Milenković, A., & Vučićević, N. (2026) · Informatics · doi:10.3390/informatics13040063 · Cited by 3
Ratniyom, J., Boonphadung, S., Intaraprasit, M., & Chumkaeo, P. (2026) · Chemistry Teacher International · doi:10.1515/cti-2025-0097 · Cited by 2
Jiang, M., Tang, S., & Wang, Q. N. (2026) · Sustainability · doi:10.3390/su18094278
The Cognitive Impact of AI Chatbots Dependency Among Students
Chandra, W., & Effendi, A. (2026) · International Symposium on Computational and Business Intelligence (ISCBI) · doi:10.1109/iscbi69404.2026.11495611
Examining the Influence of ChatGPT on Programming Courses in Higher Education
Prado, J., & Palaoag, T. D. (2026) · International Conference on Advances in Artificial Intelligence and Machine Learning (AAIML) · doi:10.1109/aaiml67890.2026.11498114
Generative AI for Education in Infrastructure Systems: Lessons from a BIM-Based Rule-Checking
Sahraoui, I., Kim, K., Gao, L., Din, Z. U., & Senouci, A. (2026) · Computers · doi:10.3390/computers15050289
ChatGPT in research and practice: Insights into applications, challenges, and future prospects
Tôn, N. T. H., VALLE, L., Latifah, K., Anwar, M. T., & Bhandari, R. (2026) · Multidisciplinary Reviews · doi:10.31893/multirev.2026524
AI Curricula in Primary and Early Childhood Education: A Cross-Country Analysis of Implementation
Aranda, G., & Ferguson, J. P. (2026) · Springer eBooks · doi:10.1007/978-3-032-12174-5_11
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Dines, N., & Mokryn, O. (2026) · Annual Symposium on HCI Education (EduCHI) · doi:10.1145/3803869.3803887
Ren, N.-L., & Tse, A. W. C. (2025) · International Conference on Education and E-Learning (ICEEL) · doi:10.1145/3789859.3789907
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Stamatiou, E. (2026) · Journal of Theatre Dance and Performance Training · doi:10.1080/19443927.2026.2661791
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Metadata
- Authors
- Lo, C. K., Hew, K. F., & Jong, M. S.-Y.
- Affiliations
- Education University of Hong Kong (HK)
- University of Hong Kong (HK)
- Chinese University of Hong Kong (HK)
- Corresponding author
- Lo, Chung Kwan
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 219
- Pages
- 105100
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W4399455976
- Semantic Scholar
- e407f4afa951efeb990ac543e22a83d48fd0a915
- Cited by
- 392
- References
- 108
- Citations by year
- 2026: 190 · 2025: 176 · 2024: 26
- FWCI
- 23.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Computers & Education (publishedVersion, cc-by-nc)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion, cc-by-nc-nd)
- 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, student engagement, AI chatbots in education, academic dishonesty, behavioral engagement, emotional engagement, cognitive engagement, student satisfaction, critical thinking, overreliance on AI, self-regulation, study habits, student attendance, social interaction
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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 ›
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