在知识结构理论中的可靠性衡量标准
Debora de Chiusole1, Andrea Spoto2,3,4, Umberto Granziol2,4
1FISPPA Department, University of Padua, Padua, Italy.
The British journal of mathematical and statistical psychology
|November 1, 2025
概括
本研究介绍了预期的准确率和预期的差异,以评估知识结构理论 (KST) 中的知识状态估计可靠性. 结果显示,KST评估为教育和心理测试提供了可靠的诊断信息.
科学领域:
- 教育测量教育的测量
- 心理测量 心理测量 心理测量
- 认知科学 认知科学
背景情况:
- 知识结构理论 (KST) 为理解知识表示提供了一个框架.
- 可靠的知识状态估计对于有效的诊断评估至关重要.
- 现有的方法可能无法完全捕捉估计准确性和错误的细微差别.
研究的目的:
- 在KST框架内评估知识状态估计的可靠性.
- 引入和定义两个新的指标:预期准确率和预期差异.
- 证明这些措施在教育和心理测试中的实际实用性.
主要方法:
- 开发预期准确率和预期差异的理论定义.
- 进行两项模拟研究,分析在不同条件下测量性能.
- 将这些措施应用于从现实世界的评估中获得的经验数据集.
主要成果:
- 在项目数量和知识结构大小之间存在权衡.
- 较小的结构显示一致的准确性,而较大的结构可能会有越来越多的差异与更高的错误率.
- 在更大的结构中,随着更多项目的增加,准确性会提高,在错误分类时,估计状态通常接近真实状态.
结论:
- 拟议的措施 (预期准确率和预期差异) 提供了一种可靠的方式来评估知识状态估计.
- 基于KST的评估产生了有意义的诊断信息.
- 这些发现支持在教育和心理测试中使用KST,以改善诊断.
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