解释性认知诊断模型包含项目特征
Manqian Liao1, Hong Jiao2, Qiwei He3
1Duolingo, Inc., 5900 Penn Ave, Pittsburgh, PA 15206, USA.
Journal of Intelligence
|March 27, 2024
概括
本研究介绍了项目解释性认知诊断模型 (CDM),以改善项目质量评估. 通过将项目参数与语言特征联系起来,这些模型为增强测试项目提供了更好的洞察力.
科学领域:
- 心理测量 心理测量 心理测量
- 教育测量教育的测量
- 认知诊断是一种认知诊断.
背景情况:
- 项目质量对于认知诊断中准确的心理测量分析至关重要.
- 传统的认知诊断模型 (CDM) 仅使用项目响应数据,使低质量的项目的识别和改进变得复杂.
- 挑战包括确定诸如高猜测概率或改善项目质量的困难等问题.
研究的目的:
- 提出项目解释性CDM,将项目特征与项目参数集成在一起.
- 为了利用项目特征作为校准CDM参数的额外信息来源.
- 提高认知诊断中的物品质量的理解和改进.
主要方法:
- 开发了项目解释性认知诊断模型 (CDM).
- 使用自然语言处理技术从项目茎中提取了大约20个语言特征.
- 将模型应用于国际数学和科学研究 (TIMSS) 的数据趋势,使用更高阶的DINA模型分析项目参数和特征之间的关系.
主要成果:
- 用现实数据展示了项目解释性CDM的实用性.
- 确定了猜测/滑动参数和特定项目的特征之间的关系.
- 一项模拟研究证实了经验数据分析的发现.
结论:
- 项目解释性CDM为了解和提高项目质量提供了有价值的框架.
- 整合项目特征为心理测量分析提供了更丰富的方法,而不是仅仅依赖于响应数据.
- 这种方法促进了针对性的项目开发和改进,以便更好地进行诊断评估.
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