一个整体的框架,以模拟学生的认知过程在数学教育通过模糊的认知地图的数学教育
1University of Salerno, Giovanni Paolo II street 84100, Fisciano, SA, Italy.
Heliyon
|September 4, 2024
概括
这项研究使用模糊认知地图 (FCM) 来建模学生的数学认知,整合多种学习理论以获得整体观点. 该框架提供了对数学学习中的认知,情感和行为因素的定量见解.
科学领域:
- 教育心理学教育心理学
- 认知科学 认知科学
- 数学教育教育 数学教育
背景情况:
- 传统的数学教育研究往往依赖于定性方法.
- 越来越需要量化方法来理解学生复杂的认知过程.
- 数字学习环境需要对学生互动进行实时分析.
研究的目的:
- 在数学教育中使用模糊认知地图 (FCM) 引入一种用于模拟学生认知过程的新框架.
- 通过整合认知,情感和行为因素,为学生的数学学习提供全面,多维的理解.
- 证明FCM在从教育数据中产生定量见解方面的实用性.
主要方法:
- 发展一个模糊的认知地图 (FCM) 模型,整合杜瓦尔的语义表示理论,尼斯的数学能力,马顿的变化理论,以及参与,动机和参与框架.
- 在案例研究中应用FCM模型,包括分析COVID-19大流行期间的远程学习以及增强现实在概念化中的作用.
- 通过定性方法验证定量FCM数据.
主要成果:
- FCM框架成功地模拟了学生的认知过程,通过整合各种教育理论,提供了整体的观点.
- 案例研究表明,该框架在分析远程学习的影响和增强现实在数学中的潜力方面具有适应性.
- 从FCM模型中获得的定量数据得到了定性发现的证实.
结论:
- 模糊的认知地图为数学教育中认知过程的定量分析提供了先进的方法创新.
- 该框架有可能整合新技术并增强教育实践,特别是在数字学习环境中.
- 需要进一步的研究来解决方法转型和技术实施挑战,以获得更广泛的适用性.
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