在八年级学生中构建因子化的认知模型的实证研究
Xu Zhangtao1, Cai Jiabao1, Li Jiale1
1School of Mathematics and Statistics, Central China Normal University, Wuhan, China.
Frontiers in psychology
|July 24, 2023
概括
这项研究开发了一种用于数学诊断的认知因子化模型. 结果显示,学生对因子分解的掌握程度各不相同,创新率最低. 这个模型有助于理解学生的数学能力.
科学领域:
- 认知科学是一种认知科学.
- 教育心理学教育心理学
- 数学教育的数学教育.
背景情况:
- 认知模型是认知诊断的基础.
- 模型必须根据特定的教育目标进行定制,例如数学能力和知识维度.
研究的目的:
- 构建和验证用于数学教育的认知因子化模型.
- 为了诊断八年级学生对因数分解和数学运算能力的掌握.
主要方法:
- 使用专家输入和文献评论构建了一个认知因子化模型.
- 通过口头报告和项目难度回归与认知属性对模型进行验证.
- 评估了武汉两个班级的72名八年级学生.
主要成果:
- 认知因子化模型被发现是合理和有效的诊断.
- 79%的学生表现出对因数分解知识的理解.
- 71%的人实现了知识转移,而只有28%的人实现了知识创新.
结论:
- 开发的认知因子化模型是评估数学技能的有效工具.
- 学生的表现在不同的认知水平上有所不同,突出了针对性干预的需要,特别是在知识创新方面.
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