基于变压器的嵌入方法来开发简短的心理测量
1Department of Psychology, Jeonbuk National University, Jeonju, Republic of Korea.
Frontiers in psychology
|August 29, 2025
概括
这项研究引入了一种使用人工智能的语义嵌入来创建更短的心理调查的新方法. 这种方法有效地减少了项目,同时保持了强大的心理测量特性,为心理测量开发提供了数据独立的替代方案.
科学领域:
- 心理测量
- 人工智能
- 自然语言处理
背景情况:
- 开发简短的心理措施对于减少参与者负担和资源支出至关重要.
- 现有的简体形式开发方法通常需要使用因子分析或机器学习进行广泛的数据收集和分析.
- 需要有效的,数据独立的方法来减少心理项目.
研究的目的:
- 通过基于变压器的语义嵌入来提出和评估一种新的,数据独立的心理项目减少方法.
- 使用这种新的方法开发国际人格项目池五大因素标记 (IPIP-50) 的简体版本.
- 将开发的简体形式的心理测量特性与现有方法进行比较.
主要方法:
- 使用基于变压器的语义嵌入 (句子-t5-xxl模型) 来表示IPIP-50中的项目.
- 应用K-意味着对语义嵌入进行聚类,以组合相似的项目.
- 根据它们与集群中心的近距离选择了代表性项目,以形成30项的简短形式.
主要成果:
- 由此产生的30项简短形式成功地保留了IPIP-50的原始五要素结构.
- 简短的形式显示出强大的心理特征,包括可靠性和有效性.
- 拟议的方法实现了与古典测试理论和遗传算法方法相比的可靠性,收有效性和预测性能.
结论:
- 基于转换器的语义嵌入为心理项目减少和新措施的开发提供了强大而有效的方法.
- 这种数据独立的方法提供了基于语言的,资源高效的替代传统数据依赖的减少技术.
- 这些发现支持使用人工智能开发强大而简洁的心理评估的可行性.
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