From self-regulated to hybrid regulated learning: a framework Free
The rapid integration of artificial intelligence into education is reshaping what it means to learn, to know and to teach. Traditional models such as self-regulated learning assume that learners plan, monitor and evaluate their own learning. In AI-rich environments, however, these processes are increasingly shared with systems that generate feedback, structure tasks, and influence decisions.
In this talk, Dr Hayo Reinders argues that we are moving toward hybrid-regulated learning, where control is negotiated between human and AI. Drawing on examples from language education, Dr Reinders shows how practices such as AI-assisted writing, conversational agents and learning analytics are redistributing agency and subtly shaping learner behaviour.
To make sense of this shift, he introduces a framework that focuses on three elements: the roles AI plays in learning processes, the literacies learners need to engage with these systems critically, and the use of artefacts to make learning visible beyond final outputs. These provide a basis for maintaining human agency in distributed learning environments.
The implications are significant. Educators must move from delivering content to designing conditions for effective human-AI regulation, while institutions need to rethink assumptions about autonomy, assessment and integrity. Rather than resisting technological change, Dr Reinders argues for a redefinition of how learning is regulated and valued in an AI-mediated world.
Dr Hayo Reinders is Senior Professor of TESOL and Director of Research at Anaheim University in the USA and founder of the Institute for Teacher Leadership. He is editor of Innovation in Language Learning & Teaching and Language Learning & Technology.