While Generative Artificial Intelligence (GenAI) has transformative potential for collaborative learning, it may also induce cognitive offloading and superficial consensus, leading learners to accept AI-generated outputs uncritically. To address these risks, this study developed metacognitive scaffolds for triadic “Learner–Peer–GenAI” interaction to foster critical thinking. An eight-week quasi-experimental intervention was conducted with 85 sixth-grade students, comparing an experimental group receiving scaffolds (n = 42) with a control group without scaffolding (n = 43). Using a multi-method design involving pre/post tests, SOLO-based cognitive-structure analysis, Epistemic Network Analysis (ENA), and Lag Sequential Analysis (LSA), we examined changes in critical-thinking performance, cognitive structure, and interaction trajectories. Results showed that the experimental group significantly outperformed the control group in overall critical thinking and three dimensions: questioning and verification, logical reasoning, and reflection and regulation, with the largest gains in questioning and verification. High-order cognitive structures accounted for 49.7% of the experimental group’s discourse, indicating a shift toward higher-level thinking. Behavioral analyses identified a dominant sequence—Questioning (QB.AI)→Evidence Retrieval (ER.AI)→Logical Analysis (LA.AI)—and a more cohesive epistemic network, whereas the control group showed surface-level exchange and passive agreement. These findings suggest that metacognitive scaffolding can regulate GenAI-supported collaboration, preserve learner agency, and promote cognitive reciprocity.
Zhuo et al. (Mon,) studied this question.