Development and validation of generative artificial intelligence attitude scale for students

Introduction Generative artificial intelligence (AI) tools, such as ChatGPT, have gained significant traction in educational settings, offering novel opportunities for enhanced learning experiences. However, limited research has investigated how students perceive and accept these emerging technologies. This study addresses this gap by developing a scale to assess university students’ attitudes toward generative AI tools in education. Methods A three-stage process was employed to develop and validate the Generative AI Attitude Scale. Data were collected from 664 students from various faculties during the 2022–2023 academic year. Expert evaluations were conducted to establish face and content validity. An exploratory factor analysis (EFA) was performed on a subset of 400 participants, revealing a two-factor, 14-item structure that explained 78.440% of the variance. A subsequent confirmatory factor analysis (CFA) was conducted on a separate sample of 264 students to validate this structure, resulting in the removal of one item and a final 13-item scale. Results The 13-item scale demonstrated strong reliability, evidenced by a Cronbach’s alpha of 0.84 and a test–retest reliability of 0.90. Discriminative power was confirmed through corrected item-total correlations between lower and upper percentile groups. These findings indicate that the scale effectively differentiates student attitudes toward generative AI tools in educational contexts. Discussion The newly developed Generative AI Attitude Scale offers a valid and reliable instrument for measuring university students’ perspectives on integrating generative AI tools, such as ChatGPT, into educational environments. These results highlight the potential for more targeted research and informed implementation strategies to enhance learning outcomes through generative AI.