Abstract
Artificial intelligence (AI) is increasingly exploited to promote student engagement. This study combined topic modelling, keyword analysis, trend test and systematic analysis methodologies to analyse AI-supported student engagement (AIsE) studies regarding research keywords and topics, AI roles, AI systems and algorithms, methods and domains, samples and outcomes. Findings included the following: (1) frequent-used and emerging keywords comprised ‘machine learning’, ‘artificial intelligence chatbot’ and ‘collaborative knowledge building’. (2) Frequently studied topics included ‘AI for MOOCs and self-regulated learning’ and ‘affective computing and emotional engagement’. (3) Most studies adopted intelligent tutoring systems, traditional machine learning methods and natural language processing. (4) Emotional engagement regarding affective or psychological states among college students received the most attention. (5) Most studies adopted quantitative approaches and concerned computer science and language education. Accordingly, we highlighted AI's roles as tutors, advisors, partners, tutees and regulators for behavioural, cognitive and emotional engagement to inspire AI's effective integration into education.
Original language | English |
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Article number | e70008 |
Journal | European Journal of Education |
Volume | 60 |
Issue number | 1 |
Early online date | 31 Jan 2025 |
DOIs | |
Publication status | E-pub ahead of print - 31 Jan 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Author(s). European Journal of Education published by John Wiley & Sons Ltd.
Keywords
- applications
- artificial intelligence
- student engagement
- systematic review
- text mining
- trends