The authors introduce Agentivism as a learning theory for human-AI interaction that explains how durable capability develops through selective delegation, epistemic monitoring, reconstructive internalization, and transfer under reduced support.
Unveiling interaction patterns between students and generative AI teachable agents: Focusing on students’ agency and AI agents’ authority
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A human-reviewed AI-in-the-loop system in cMOOCs selectively improves social presence and higher-order cognitive presence via reciprocal interaction and adaptive roles rather than AI co-presence.
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Agentivism: a learning theory for the age of artificial intelligence
The authors introduce Agentivism as a learning theory for human-AI interaction that explains how durable capability develops through selective delegation, epistemic monitoring, reconstructive internalization, and transfer under reduced support.