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<p>In the context of accelerating integration of artificial intelligence (AI) technologies into education, rapidly assessing students’ AI attitude is crucial for advancing digital transformation in education.</p><p>The aim of this study is to develop and validate a new five-item version of the Artificial Intelligence Attitude Scale (AIAT-5). For examining the quality of the scale, a total sample of 1576 middle and high school students (study 1: 858; study 2: 614) from diverse regions in China completed the survey. Results: (1) Study1: AIAT-5 exhibited strong internal consistency (Cronbach’s α = 0.923, McDonald’s ω = 0.923, Guttman’s λ6 = 0.911) and good discrimination (<i>α</i> = 3.201 ~ 4.513). Both EFA and EGA supported a robust unidimensional structure. (2) Study 2: CFA results indicated excellent model fit for unidimensional structure (CFI = 0.993, TLI = 0.976, and RMSEA = 0.028), and all factor loadings ranged from 0.879 to 0.953. Furthermore, AI attitude was positively correlated with knowledge of generative AI, life satisfaction, internet addiction, and epistemic curiosity. Overall, within the specific population of Chinese middle and high school students, the AIAT‑5 demonstrates initial validation as a reliable and practically efficient tool for large‑scale assessment of student AI attitude.</p>

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Development and psychometric analysis of 5-item Artificial Intelligence Attitude (AIAT-5) for students

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Guogang Xin,
  • Shengqin Yang,
  • Xiaoyu Hou,
  • Ruobing Wang,
  • Shuaishuai Mi,
  • Jipeng Wang,
  • Bing Shen

摘要

In the context of accelerating integration of artificial intelligence (AI) technologies into education, rapidly assessing students’ AI attitude is crucial for advancing digital transformation in education.

The aim of this study is to develop and validate a new five-item version of the Artificial Intelligence Attitude Scale (AIAT-5). For examining the quality of the scale, a total sample of 1576 middle and high school students (study 1: 858; study 2: 614) from diverse regions in China completed the survey. Results: (1) Study1: AIAT-5 exhibited strong internal consistency (Cronbach’s α = 0.923, McDonald’s ω = 0.923, Guttman’s λ6 = 0.911) and good discrimination (α = 3.201 ~ 4.513). Both EFA and EGA supported a robust unidimensional structure. (2) Study 2: CFA results indicated excellent model fit for unidimensional structure (CFI = 0.993, TLI = 0.976, and RMSEA = 0.028), and all factor loadings ranged from 0.879 to 0.953. Furthermore, AI attitude was positively correlated with knowledge of generative AI, life satisfaction, internet addiction, and epistemic curiosity. Overall, within the specific population of Chinese middle and high school students, the AIAT‑5 demonstrates initial validation as a reliable and practically efficient tool for large‑scale assessment of student AI attitude.