Future AI-SRL research should broaden search strategies, include educators and younger learners, address motivation, and apply longitudinal designs¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Based on identified gaps, the review recommends that future reviews use "broader search strategies, such as keyword expansion or full-text searches, to provide a more inclusive representation of the literature". It further recommends longitudinal research to assess long-term impacts of AI on SRL, more global participation to bring diverse perspectives, greater attention to the motivational aspect of SRL, and inclusion of educators, who are described as crucial in implementing SRL strategies. It also recommends a full quality appraisal of studies in any future full systematic review.

Design Implications¶

Context¶

Requirements¶

• Future reviews should conduct a full quality appraisal of included studies

Constraints¶

• The review notes its own strategy's Global North geographical and linguistic bias and that restricting keywords to title or abstract may have excluded relevant work

Target Learners¶

• higher education students
• primary and secondary students
• educators

Target Learning Goals¶

• self-regulated learning
• motivation
• long-term effects of AI support

Related Strategies¶

• Adopt more precise terminology such as digital personalized learning (DPL) or personalized adaptive learning, and pursue rigorous longitudinal research with younger learners
• Adopt a conservative abstract-screening strategy with a 'maybe' category and keyword exclusion filters to prevent premature exclusion
• Adopt unified KPIs and rigorously assess learner diversity, recommender fairness, and long-term engagement when evaluating ITS
• Diversify AIED: use diverse technologies, address big problems, and reuse existing resources rather than reinventing content
• Future shared story reading research should extend to nonfiction texts, inclusive settings, and include practicality statements
• Research and practice recommendations: activate knowledge during and after reading, study narrative texts and younger learners, and clarify definitions
• Broaden search terminology and bibliographic databases in future eWIL reviews
• Use broad and specific keywords and develop methodological search filters to improve retrieval of arts-based research

Examples¶

-

Key Sources¶

• Banihashem, S. K., Bond, M., Bergdahl, N., Khosravi, H., & Noroozi, O. (2025). A systematic mapping review at the intersection of artificial intelligence and self-regulated learning. International Journal of Educational Technology in Higher Education, 22(50). https://doi.org/10.1186/s41239-025-00548-8