Lintner Tomáš
Department of Educational Sciences, Faculty of Arts, Masaryk University, Brno, Czech Republic.
Institute SYRI, Brno, Czech Republic.
NPJ Sci Learn. 2024 Aug 6;9(1):50. doi: 10.1038/s41539-024-00264-4.
With the opportunities and challenges stemming from the artificial intelligence developments and its integration into society, AI literacy becomes a key concern. Utilizing quality AI literacy instruments is crucial for understanding and promoting AI literacy development. This systematic review assessed the quality of AI literacy scales using the COSMIN tool aiming to aid researchers in choosing instruments for AI literacy assessment. This review identified 22 studies validating 16 scales targeting various populations including general population, higher education students, secondary education students, and teachers. Overall, the scales demonstrated good structural validity and internal consistency. On the other hand, only a few have been tested for content validity, reliability, construct validity, and responsiveness. None of the scales have been tested for cross-cultural validity and measurement error. Most studies did not report any interpretability indicators and almost none had raw data available. There are 3 performance-based scale available, compared to 13 self-report scales.
随着人工智能发展及其融入社会所带来的机遇和挑战，人工智能素养成为一个关键问题。使用高质量的人工智能素养工具对于理解和促进人工智能素养发展至关重要。本系统评价使用COSMIN工具评估了人工智能素养量表的质量，旨在帮助研究人员选择人工智能素养评估工具。本评价确定了22项验证16个量表的研究，这些量表针对不同人群，包括普通人群、高等教育学生、中等教育学生和教师。总体而言，这些量表显示出良好的结构效度和内部一致性。另一方面，只有少数量表进行了内容效度、信度、结构效度和反应度测试。没有一个量表进行过跨文化效度和测量误差测试。大多数研究没有报告任何可解释性指标，几乎没有研究提供原始数据。有3个基于表现的量表，而自我报告量表有13个。
