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Updated: Aug 20, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
Published on: September 27, 2020
AI-Assisted Student-Centered Instruction and Adolescents' Academic Self-Concept and Communication Competence: A
Lingyun Deng1, Shanshan Han2, Fengni Yang3
1College of Education, Kookmin University.
None:
This classroom-based mixed-methods quasi-experimental study examined whether AI-assisted student-centered instruction was associated with changes in adolescents' academic self-concept and self-reported communication competence. Six intact classes were assigned to either the AI-assisted instruction or the usual student-centered instruction condition. The intervention embedded AI-supported prompts into a structured learning cycle comprising individual inquiry, peer discussion, teacher clarification, and self-evaluation. Of the 186 recruited students, 174 were retained for quantitative analysis. Academic self-concept and self-reported communication competence were assessed at baseline, immediately after the intervention, and at a predefined short-term follow-up. Interaction quality, self-evaluation, and learner engagement were measured after the intervention, and 36 students participated in semi-structured interviews. Compared with the usual instruction group, the AI-assisted group showed larger baseline-adjusted gains in both outcomes at post-intervention and follow-up. Exploratory process analyses indicated higher interaction quality, self-evaluation, and learner engagement in the AI-assisted group, while qualitative findings suggested that AI-supported prompts helped students to verify explanations, revise responses, and make self-evaluation more explicit when combined with peer discussion and teacher guidance. Because participants were assigned at the class level and outcomes were primarily self-reported, the findings should be interpreted as classroom-based associations rather than definitive evidence of a causal improvement in academic performance.
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