English(EN) Using Machine Learning to Measure Self-Efficacy Belief Through Learners' Interaction Traces in Technology-Enhanced Learning

机器学习模型从学习互动中检测学生自我效能

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员开发了一个机器学习系统，通过分析学生在技术增强型学习环境中的互动痕迹来检测其低自我效能信念。这项探索性研究在两所大学进行，收集了学生互动和自我报告的自我效能数据。研究结果强调了自我效能的动态性质以及持续监控对于准确预测的重要性。 AI

影响这项研究可能通过实现对学生信心问题的早期检测，从而带来更具个性化和支持性的教育工具。

排序理由这是一篇研究论文，详细介绍了机器学习在特定教育问题上的新颖应用。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Maeva Somny (LIRIS), Linda Chouati, Marie Lefevre · 2026-11-02 05:00

利用机器学习通过技术增强学习中学习者的互动痕迹来衡量自我效能信念

arXiv:2610.41900v1 Announce Type: new Abstract: Self-efficacy beliefs play a critical role in learners' performance, academic choices, and, more broadly, in their future career trajectories. As Technology-Enhanced Learning (TEL) environments have demonstrated strong potential for…