Use metacognitive activities and process evidence to help students monitor the purpose of their AI use¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article proposes educational practices that shift attention from how often students use AI to why they use it, helping students recognize avoidance-driven engagement. Suggested tools include "reflective prompts, process-based assessment, and AI-use logs" and encouraging students to generate initial ideas independently before consulting AI. The authors frame these as proposals warranting future empirical evaluation rather than validated interventions.

Design Implications¶

Context¶

Requirements¶

• Strategies require systematic empirical evaluation before implementation, as the authors state

Constraints¶

• Derived from cross-sectional, self-report findings; effectiveness not yet tested

Target Learners¶

• Chinese university students
• higher education students using AI tools

Target Learning Goals¶

• maintaining active engagement with cognitively demanding creative tasks
• self-regulated AI use

Related Strategies¶

• Design activities that make students' AI-supported learning processes visible through reflection prompts and process documentation

Examples¶

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Key Sources¶

• Hou Jie, Huang Yanhong, Wang Qing, Yao Xiaoxue, Zhang Peizheng, Zhao Fengqing. (2026). AI Dependence and Self-Reported Creativity Among Chinese College Students: The Roles of Motivation for AI Use and Perceived AI Literacy. Behavioral Sciences, 16(9), 1712. https://doi.org/10.3390/bs16091712