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Introduction Generative AI can facilitate the production of student work but may also displace learners' responsibility for problem framing, evaluation, and revision. This study examined whether design-thinking scaffolds were associated with creative self-efficacy, cognitive flexibility, and problem-solving engagement during AI-supported project learning. Methods A three-condition, four-wave quasi-experimental study included 162 undergraduates in six intact class sections (54 per condition). Non-AI project learning, ordinary GenAI use, and design-thinking-scaffolded GenAI use were compared across a four-week educational design task. Baseline-adjusted models assessed self-reported outcomes, human-coded AI-use logs, and independently rated products from 54 teams. Cluster-bootstrap analyses examined temporally ordered indirect associations and moderation by pre-intervention AI over-reliance. Results Compared with ordinary GenAI, the scaffolded condition showed higher T2 creative self-efficacy (adjusted difference = 0.33, p = 0.006), T3 cognitive flexibility (0.35, p = 0.003), and T4 engagement (0.35, p = 0.004). Mean team product quality was 20.14 in the scaffolded condition, compared with 17.62 under ordinary GenAI and 16.76 without AI. Coded prompts showed fewer answer-completion requests and more comparison, critique, and reflection. Indirect estimates via creative self-efficacy (0.07), cognitive flexibility (0.09), and their sequential pathway (0.04) had bootstrap confidence intervals excluding zero. Higher initial AI over-reliance weakened the overall engagement contrast and the two single-mediator indirect pathways, whereas the moderated-sequential index had a confidence interval including zero. Discussion The findings are consistent with agency-preserving cognitive offloading when instructional scaffolds retain student responsibility for higher-order decisions. Intact-section allocation, task-specific self-reports, and limited section-level replication preclude strong causal or general-transfer claims.
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Yueyong Wang (2026) studied this question.
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