GenAI ‐based metacognitive prompting in collaborative inquiry: A comparison across diverse preconception groups

Generative AI (GenAI) is increasingly integrated into collaborative inquiry to provide metacognitive prompting that scaffolds socially shared regulation of learning (SSRL). Understanding how such GenAI‐based metacognitive prompting is taken up through student–GenAI interactions is therefore critical. However, although learner–GenAI interaction processes have been widely examined, little is known about how learners' preconceptions shape their engagement with GenAI‐based metacognitive prompting. This study examined how groups with different or similar preconceptions about energy forms and conservation differed in their engagement with GenAI‐based metacognitive prompting during collaborative inquiry. Participants comprised 14 small groups, including eight groups with different preconceptions (D groups) and six groups with similar preconceptions (S groups). The distribution of learner‐generated inquiries directed to the written metacognitive AI (MAI) was largely comparable across groups. Lag sequential analysis revealed contrasting patterns in how groups evaluated the metacognitive prompts: D groups showed sustained positive or neutral evaluation of the prompts, whereas S groups showed sustained negative evaluation. Process mining further showed that AI query negotiation served as a hub in D groups' collaboration, connecting their conceptual discussions and task coordination. In S groups, by contrast, it formed part of a simpler, linear sequence of querying the AI and processing its responses. This study advances understanding of how preconception diversity shapes the processes and dynamics of human–AI collaboration. The findings show that AI‐mediated regulation varies depending on group‐level knowledge configurations.

What is already known about this topic

Effective collaborative inquiry depends on learners' prior knowledge resources and their regulatory capacity.