邻里集群的代项目选择:一种非参数和非IRT方法,用于生成微型计算机适应性问卷
1Beijing Normal University, Zhuhai, China.
Educational and psychological measurement
|June 20, 2024
概括
计算机自适应测试 (CAT) 为漫长的心理问卷提供了解决方案. 这种新的非参数,对象响应理论独立的CAT算法是可概括的,并为各种测试验证.
科学领域:
- 心理测量方法 心理测量方法
- 心理测量 心理测量 心理测量
- 计算机适应性测试 计算机适应性测试
背景情况:
- 问卷在心理学中至关重要,但增加长度会影响数据质量和收集效率.
- 现有的计算机自适应测试 (CAT) 方法通常是参数式的,需要特定的模型和心理测量预试.
研究的目的:
- 为心理问卷提出一种新的,非参数的,与物品响应理论 (IRT) 独立的CAT算法.
- 开发一种可通用且易于应用的CAT方法,绕过理论假设.
主要方法:
- 开发一种新的非参数式CAT算法.
- 算法设计独立于项目响应理论 (IRT) 假设.
- 通过模拟和实证研究对能力和个性措施的验证.
主要成果:
- 拟议的非参数CAT算法在模拟和实证研究中都显示出有效性.
- 该算法在适应性测试和人格测量中被证明是有效的.
- 简单性和通用性是新的CAT方法的关键特征.
结论:
- 新的非参数式,与IRT独立的CAT算法为心理测量提供了灵活和高效的替代方案.
- 这种方法可以减少问卷的长度,同时保持测量准确度,适用于各种研究领域.
- 该方法的通用性消除了对具体问题的广泛建模或预试验的需要.
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