在复杂的问题解决任务中的多种有效性指标及其在开发测量模型中的应用
Pujue Wang1,2, Hongyun Liu3,4
1Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing, 100875, China.
Psychometrika
|April 9, 2024
概括
本研究引入了多种有效性指标,用于分析复杂的问题解决任务,改进心理测量过程模型. 新的顺序响应模型与多种有效性指标 (SRM-PEI) 提供了对用户能力和任务转换的更好的洞察力.
科学领域:
- 心理测量 心理测量 心理测量
- 认知科学 认知科学
- 教育技术的教育技术
背景情况:
- 目前用于交互任务的心理测量过程模型往往简化了状态过渡到二分法指标.
- 这种简化对于具有多个最佳路径和众多过渡的复杂问题是不够的.
研究的目的:
- 在交互式任务中引入多种指标来评估问题状态和过渡.
- 提出一种新的心理测量过程模型,SRM-PEI,适应复杂的问题解决场景.
主要方法:
- 开发了多种类型的有效性指标的三步评估方法.
- 引入了具有多种有效性指标 (SRM-PEI) 的顺序响应模型.
- 使用蒙特卡洛模拟和实证研究对两个真实世界的任务验证了模型.
主要成果:
- 在估计潜在能力和过渡趋势参数方面,SRM-PEI表现强.
- 经验研究表明,SRM-PEI提供了比以前的模型 (SRM,SRMM) 更好的匹配.
- 有效性指标给出了潜在能力和过渡趋势的合理和可解释的估计.
结论:
- 多种有效性指标和SRM-PEI增强了复杂问题解决任务的分析.
- 拟议的模型提供了对交互式环境中用户行为的更细致的理解.
- 未来的研究可以探索多种类型指标和SRM-PEI的进一步应用和增强.
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