使用生成性人工智能开发和改进人格库存:使用ChatGPT 4.0开发的简短HEXACO尺度的心理测量属性
Ard J Barends1, Reinout E de Vries2
1Institute for Criminal Law and Criminology, Leiden, Leiden University, Leiden, The Netherlands.
Journal of personality assessment
|December 27, 2024
概括
生成型人工智能在创建像ChatGPT HEXACO库存 (CHI) 这样的人格调查方面表现有前途. 然而,它无法增强CHI的心理测量特性,这表明人工智能不是改善调查质量的捷径.
科学领域:
- 心理评估 心理评估 心理评估
- 在研究中的人工智能.
- 调查方法调查方法.
背景情况:
- 像ChatGPT这样的生成性AI工具为研究提供了新的可能性.
- 开发可靠和有效的人格库存对于心理学研究至关重要.
- 之前的研究还没有广泛探索AI在调查改进中的实用性.
研究的目的:
- 评估生成AI在创建和改进人格调查方面的有效性.
- 评估ChatGPT是否可以提高产生的库存的内部一致性和内容有效性.
- 将人工智能产生的库存的心理特征与现有的测量方法进行比较.
主要方法:
- 使用ChatGPT 4.0 (ChatGPT HEXACO库存 - CHI) 创建了一个24项HEXACO人格库存.
- 聊天GPT被要求修改CHI以改善心理测量属性.
- 三个CHI版本与简要的HEXACO库存 (BHI) 进行了比较,使用了心理测量分析 (可靠性,相关性).
主要成果:
- 这三种CHI版本的心理测量特性与BHI的心理测量特性普遍相似.
- 聊天GPT无法显著提高CHI的内部一致性或内容有效性.
- 收性和歧视性有效性相关性在CHI版本和BHI中普遍相似.
结论:
- 生成型人工智能显示出初始调查开发的潜力.
- 目前,人工智能并没有为提炼问卷的特定心理测量特性提供捷径.
- 需要进一步的研究来优化AI在心理评估工具开发中的作用.
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