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- Vol 4 RE: Chapters 25, 27
artificial intelligenceself-regulated learningintelligent tutoring systemslearning analyticsconversational agentsadaptive learningmetacognitive regulationlearner agencyJournal article Evidence summaryAt a glance
Ren, Lee, and May systematically review how artificial intelligence has been used to support self-regulated learning in education.
Key ideas
Searching literature from 2004 through 2024, they retain twenty-seven studies and classify them by educational level, research method, subject area, AI technology, self-regulated-learning framework, and reported outcome. The review identifies intelligent tutoring and adaptive systems, learning analytics and prediction, conversational agents, and other data-driven supports that can prompt planning, monitoring, feedback use, strategy adjustment, and reflection. It also finds uneven theoretical grounding and limited evidence across contexts, with many studies concentrated in particular settings and phases of regulation.
Why it matters
The authors call for stronger alignment between AI functions and explicit self-regulation theory, more rigorous empirical designs, attention to learner agency and ethics, and research that tests sustained effects rather than short-term performance alone.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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