中学化学中的修订Q矩阵:一种结构方程建模方法
Shiwei Lin1, Xiaolong Zhang1, Guoxu Chen1
1Chemistry College, Changchun Normal University, Changchun, Jilin, China.
Frontiers in psychology
|October 27, 2025
概括
这项研究通过结构方程建模 (SEM) 改进了用于认知诊断的Q矩阵准确性. 与其他方法相比,优先考虑学科知识的SEM方法产生了较高的相对适应性,提高了诊断评估的可靠性.
科学领域:
- 教育测量教育的测量
- 认知心理学 认知心理学
- 化学教育 化学教育
背景情况:
- Q矩阵的准确性对于可靠的认知诊断至关重要.
- 不准确的Q矩阵是教育评估研究中常见的挑战.
- 本研究使用初中化学话题来解决Q矩阵验证的问题.
研究的目的:
- 验证和修改用于认知诊断评估工具的Q矩阵.
- 为了比较结构方程建模 (SEM) 方法与其他Q矩阵估计方法的有效性.
- 提高认知诊断评估的准确性和可靠性.
主要方法:
- 使用结构方程建模 (SEM) 进行Q矩阵验证和修订.
- 综合性定性学科分析与SEM合适指数 (例如MI,模型合适).
- 采用了通用的确定性输入,杂的"和"门 (GDINA) 模型进行比较分析.
主要成果:
- 与基准方法相比,SEM衍生的Q矩阵显示出绝对匹配度优异,相对匹配度优异.
- 虽然绝对匹配度略低于基准值,但相对匹配度表明整体结构更好.
- SEM方法的定性重点影响了,但最终改善了Q矩阵的性能.
结论:
- 结构方程建模为认知诊断中的Q矩阵验证和修订提供了一个强大的方法.
- 将学科知识与统计分析相结合,可以提高Q矩阵的质量.
- SEM方法为提高认知诊断评估准确性提供了一个有价值的替代方案.
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