Discussion on Empowering Ideas of AI-Supported Learning for the Development of Self-Regulated Learning in Higher Education

Ziye Zhang

doi:10.54097/tn5r4821

Authors

Ziye Zhang Faculty of Education, Monash University, Melbourne, VIC 3000, Australia

DOI:

https://doi.org/10.54097/tn5r4821

Keywords:

Higher Education; Artificial Intelligence-Assisted Learning; Autonomous Learning; Human-Computer Collaboration; Metacognitive Ability.

Abstract

The popularisation of artificial intelligence assisted learning tools in higher education gives new technical circumstances for the promotion of college students’ autonomous learning ability. This research studies the enabling mechanism and possible risks of AI-assisted learning for autonomous learning development from the perspective of autonomous learning theory. The study systematically reviews existing survey data and theoretical achievements, and finds that personalised resource provision can expand the breadth of autonomous learning, immediate feedback helps to enhance learners’ process-based self-monitoring, and heuristic interaction has a promoting effect on metacognitive ability. Survey results also pointed to dangers. 40.50% of the college students surveyed claimed that they were used to relying on AI when faced with difficulties, and they did not wish to study independently, and 48.06% said that over-reliance on AI contributed to the decline of independent thinking and writing abilities. Based on the above, this paper proposes to construct a human-machine collaborative path for autonomous learning, shifting the role of AI from “answerer” to “thinking guide”, and simultaneously cultivating metacognitive ability and critical thinking while providing technical assistance, so as to achieve the unity of technology empowerment and autonomous development.

Downloads

Download data is not yet available.

References

[1] Liu, Y., Cheng, S., Wang, H., & Mo, Y. (2026, July 10). Over 90% of the surveyed college students regard AI as their “all-round study companion”. China Youth Daily, 006.

[2] Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies and non-academic outcomes in higher education blended learning environments: A one decade review. Education and Information Technologies, 25(5), 3677–3704. https://doi.org/10.1007/s10639-020-10137-8

[3] 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(1), 50. https://doi.org/10.1186/s41239-025-00447-9

[4] Huang, A. Y., Lu, O. H., & Yang, S. J. (2023). Effects of artificial intelligence–enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684. https://doi.org/10.1016/j.compedu.2023.104684

[5] Steinert, S., Avila, K. E., Ruzika, S., Kuhn, J., & Küchemann, S. (2024). Harnessing large language models to develop research-based learning assistants for formative feedback. Smart Learning Environments, 11(1), 62. https://doi.org/10.1186/s40561-024-00311-7

[6] Lan, M., & Zhou, X. (2025). A qualitative systematic review on AI empowered self-regulated learning in higher education. npj Science of Learning, 10(1), 21. https://doi.org/10.1038/s41539-025-00270-8

[7] Wang, C. Y., & Lin, J. J. (2023). Utilizing artificial intelligence to support analyzing self-regulated learning: A preliminary mixed-methods evaluation from a human-centered perspective. Computers in Human Behavior, 144, 107721. https://doi.org/10.1016/j.chb.2023.107721

[8] Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), 37. https://doi.org/10.1186/s41239-023-00405-1

[9] Zhang, C., Rice, R. E., & Wang, L. H. (2026). College students’ literacy, ChatGPT activities, educational outcomes, and trust from a digital divide perspective. New Media & Society, 28(2), 673–695. https://doi.org/10.1177/1461444825114131

[10] Li, C., Cui, H., & Hagedorn, L. S. (2026). The cognitive impact of ChatGPT in higher education: A systematic review of critical and creative thinking outcomes. Computers and Education: Artificial Intelligence, 7, 100571. https://doi.org/10.1016/j.caeai.2026.100571

[11] Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00406-0