超级人工智能识字量表:进一步验证和开发一个简短版本
Martin J Koch1, Astrid Carolus1, Carolin Wienrich2
1Media Psychology, Julius-Maximilians-University Würzburg, Oswald-Külpe-Weg 82, 97074, Würzburg, Germany.
Heliyon
|November 11, 2024
概括
这项研究验证了Meta AI识字量表 (MAILS) 并开发了一个更简短的版本. 结果支持MAILS用于测量AI素养和相关心理能力的有效性.
科学领域:
- 心理测量 心理测量
- 人工智能识字 人工智能识字
背景情况:
- 人工智能素养对于社会适应不断发展的人工智能技术至关重要.
- 需要精确测量人工智能素养,以理解和促进它.
- 超级人工智能识字量表 (MAILS) 是人工智能识字能力和相关心理能力的自我评估工具.
研究的目的:
- 为Meta AI识字量表 (MAILS) 的有效性提供证据.
- 开发一个更短的,10项版本的MAILS实践应用.
- 推进对人工智能素养的理解和测量.
主要方法:
- 为了MAILS的测量目的而制定的公式.
- 在多个数据集中推导和经验测试的公理和次公理.
- 进行了确认因素分析,以验证原始和简单表格尺度.
主要成果:
- 发现了整体证据支持MAILS的有效性.
- 确定了需要进一步调查的意外发现.
- 成功开发了10项简短版本的MAILS,具有良好的模型适合性.
结论:
- 这项研究通过验证MAILS来推进人工智能识字测量方面的知识.
- 一个简洁的10项MAILS为评估AI素养提供了一个实用的工具.
- 进一步的研究是必要的,以充分验证短尺度,并探索AI素养的更广泛的关系.
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