一个有界的信心模型来预测小组工作如何影响学生的数学焦虑.
Matthew S Mizuhara1, Katherine Toms1, Maya Williams1
1Department of Mathematics and Statistics, The College of New Jersey, 2000 Pennington Road, Ewing, New Jersey 08618, USA.
Chaos (Woodbury, N.Y.)
|June 18, 2025
概括
合作学习可以减少数学焦虑,但同行互动很重要. 数学建模表明,一个最佳的组大小和随机的成员切换可以显著降低学生的数学焦虑.
科学领域:
- 教育心理学教育心理学
- 计算社会科学 计算社会科学
- 数学建模的数学建模
背景情况:
- 数学焦虑会对学生的成绩产生负面影响,并阻止学生参与STEM.
- 合作学习是减少数学焦虑的公认策略,并提供教学方面的好处.
- 群体内的同行互动可以减轻或加重数学焦虑.
研究的目的:
- 通过数学建模,探索数学焦虑中的同行互动的复杂动态.
- 模拟不同的交互类型如何影响学生的数学焦虑水平.
主要方法:
- 开发了一个修改后的黑塞尔曼-克劳塞有限的信心模型.
- 该模型结合了学生之间的吸引力和排斥性互动.
- 蒙特卡洛模拟被用来分析模型的预测.
主要成果:
- 确定了一个最佳的组大小,可以最大限度地减少平均数学焦虑.
- 证明随机组成员在特定频率上切换可以大幅减少数学焦虑.
- 该模型提供了对同行互动影响的定性预测.
结论:
- 数学建模为在合作学习环境中管理数学焦虑提供了有价值的见解.
- 团队规模和动态成员组成是缓解数学焦虑的关键因素.
- 该模型可适应未来的研究,包括额外的社会-个人变量.
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