How to Harness LLMs in Project-Based Learning: Empirical Evidence for Individual Autonomy and Moderate Constraints in Engineering Education

作者：Xiaoyu Yi, Wenkai Feng, Yali He, Fei Wang · 发表于：Systems · 年份：2025 · DOI：10.3390/systems13121112 · 被引用次数：3 · 研究领域：Innovative Teaching and Learning Methods、Intelligent Tutoring Systems and Adaptive Learning、Problem and Project Based Learning

The integration of large language models (LLMs) into project-based learning (PBL) holds significant potential for addressing enduring pedagogical challenges in engineering education, such as providing scalable, personalized support during complex problem-solving. Grounded in Self-Determination Theory (SDT), this study investigates how different LLM usage strategies impact student learning within a blended engineering geology PBL context. A one-semester quasi-experiment (N = 120) employed a 2 (usage mode: individual/shared) × 2 (interaction restriction: restricted/unrestricted) factorial design. Mixed-methods data, including surveys, interaction logs, and reflective reports, were analyzed to assess learning engagement, psychological needs satisfaction, cognitive interaction levels, and project outcomes. Results demonstrate that the individual use strategy significantly outperformed shared use in enhancing engagement, needs satisfaction, higher-order cognitive interactions, and final project scores. The restricted interaction strategy effectively served as a metacognitive scaffold, optimizing the learning process by promoting deliberate planning. Notably, individual autonomy did not undermine collaboration but enhanced it by improving the quality of individual contributions to group work. Students also developed robust critical verification habits to navigate LLM “hallucinations.” This research identifies “individual autonomy” as the core mechanism and “moderate constraint” as ...