中学学生与人工智能可教代理人在数学学习中的参与模式
Zifeng Liu1, Wanli Xing2, Bach Ngo3
1College of Education, University of Florida, Gainesville, 32611, USA.
Scientific reports
|November 20, 2025
概括
在数学中使用人工智能可教代理 (TA) 的学生表现出不同的参与度. 那些表现下降的人经常表现出被动的互动和无聊,这表明AI支持的学习设计存在挑战.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 人与计算机的交互
背景情况:
- 在数学学习中,中学生与人工智能可教代理人 (TA) 的接触尚未得到充分探索,特别是在经历绩效下降的学习者中.
- 了解学习者交互模式对于优化AI驱动的教育工具至关重要.
研究的目的:
- 为了调查与AI TA系统互动后表现改善的学生和表现下降的学生之间的参与差异.
- 用AITA分析中学数学学习者的行为,情绪和认知参与模式.
主要方法:
- 混合方法分析了来自两个子组的对话日志:拒绝组 (DG) 和改进组 (IG).
- 互动模式,行为指标 (会话,发言,完成率),情绪状态 (无聊,积极/消极情绪) 和认知参与的比较.
主要成果:
- 总局中普遍存在被动互动 (36%),与IG中的建设性互动 (62.78%) 相反.
- 与IG相比,DG表现出高的行为变化,但完成率较低 (0.35对0.58),厌倦率增加 (50.4%).
- 高度的行为活动和DG中的积极情绪有时与较低的学习收益相关,表明非任务或肤浅的参与.
结论:
- 人工智能可教的代理人带来了课堂挑战,被动互动和无聊对一些学生的学习产生了负面影响.
- 设计含义表明,TA应该支主动参与,检测无聊,并将低收益的行为转向有意义的学习.
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