A systematic review and meta-analysis of the effectiveness of Generative Artificial Intelligence (GenAI) on students’ motivation and engagement
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The rapid development of generative artificial intelligence (GenAI) technologies has revolutionized higher education, enhancing personalized learning and teaching practices. This study conducts a systematic review and meta-analysis to investigate the effects of GenAI on university students' motivation and engagement (cognitive, behavioural, emotional, and agency). By synthesizing experimental studies and applying association rule mining, the study (i) identifies significant positive impacts of GenAI on students' motivation and engagement across diverse educational settings. (ii) key moderating variables, such as subject category, learning strategy, and context of GenAI usage, are shown to influence these effects. (iii) subject category impacts cognitive and emotional engagement, while sample size moderates behavioural engagement. (iv) However, no significant moderating effects were observed on agency engagement. (v) The findings further highlight that individual and small group learning with GenAI, especially using ChatGPT, significantly enhances cognitive and emotional engagement. These findings contribute to the practical application of GenAI in higher education by offering actionable insights into optimizing learning strategies and engagement.
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Yan, Y., Liu, T., Song, L., & Wang, R. (2026) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-026-00493-4
An Exploratory Configurational Analysis of Learning-Process Engagement in AI-Supported Learning
Huang, D.-H., & Wang, Y.-C. (2026) · Applied System Innovation · doi:10.3390/asi9110220
Qi, P., Abuhassna, H., & Jiang, C. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1984018
- Authors
- Xia, Q., Li, W., Yang, Y., Weng, X., & Chiu, T. K. F.
- Affiliations
- Zhejiang University (CN)
- Ludwig-Maximilians-Universität München (DE)
- University of Science and Technology of China (CN)
- Education University of Hong Kong (HK)
- Chinese University of Hong Kong (HK)
- Corresponding author
- Weng, Xiaojing
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2025-12
- Volume
- 9
- Pages
- 100455
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4412988376
- Cited by
- 45
- References
- 83
- Citations by year
- 2026: 41 · 2025: 4
- FWCI
- 6.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- Funders
- The Education University of Hong Kong
- Topics
- Physical Sciences › Computer Science › Information Systems › 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
- generative AI, student motivation, student engagement, higher education, ChatGPT, cognitive engagement, behavioral engagement, emotional engagement, learning strategies, subject categories, small group learning, individual learning
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