缩短心理尺度:语义相似性很重要
Sevilay Kilmen1,2, Okan Bulut1
1University of Alberta, Edmonton, Canada.
Educational and psychological measurement
|February 27, 2025
概括
一种新的句子嵌入方法提供了一种切实可行的方法来缩短尺度,而不需要参与者数据. 这种方法在准确度上与传统方法相匹配,并提供对物品心理特性的洞察力.
科学领域:
- 心理测量 心理测量 心理测量
- 计算语言学 计算语言学
背景情况:
- 传统的缩写尺度需要大量的数据集,限制了其使用.
- 现有的自动化方法通常依赖于响应数据.
研究的目的:
- 引入使用句子嵌入的新型尺度缩写方法.
- 将这种方法与已建立的数据驱动技术进行比较.
- 评估语义相似性对于尺度开发的实用性.
主要方法:
- 开发了一种基于句子嵌入的缩写尺度技术.
- 在尺度项目之间利用语义相似性.
- 与两个已建立的自动缩写方法进行性能比较.
主要成果:
- 句子嵌入方法显示了可比的模型合适性,测量准确性和能力估计.
- 在项目歧视和语义相似性之间发现了负相关性.
- 语义特征可以预测心理特征,但不是反向得分的项目.
结论:
- 句子嵌入为缩写尺度提供了一个可行的,无数据的替代方案.
- 这种方法在没有大样本大小的情况下特别有用.
- 语义项目特征可以告知尺度的心理特征.
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