Adapting the Student Attitudes Toward Artificial Intelligence (SATAI) Scale for Higher Education Contexts



Author Information

Neslihan Köse, Bartın University, Türkiye
İlknur Civan Biçer, Anadolu University, Türkiye

Abstract

The growing integration of artificial intelligence into educational environments underscores the need for valid and reliable tools to assess students' attitudes toward AI across different educational levels. The purpose of this study is to adapt the Students’ Attitudes towards Artificial Intelligence (SATAI) Scale, developed by Suh and Ahn (2022) for primary and secondary education, for higher education contexts. The participants in the study were 535 undergraduate students from English Language Teaching departments at two different universities in Türkiye. Data were collected through Google Forms in two rounds: the first round for exploratory factor analysis (n1 = 325) and the second round for confirmatory factor analysis (n2 = 210). The exploratory factor analysis confirmed the original three-factor structure of the scale, which includes cognitive, affective, and behavioral components. Following this analysis, nine items were removed for the confirmatory factor analysis. The results of the confirmatory factor analysis showed a good fit, supporting the three-factor structure. Therefore, the SATAI Scale for higher education contexts (SATAI-HE) is validated as a reliable tool for measuring the attitudes of higher education students toward artificial intelligence. This study contributes to the field by offering a relevant assessment tool that can guide AI-related educational practices, policy decisions, and curriculum development in higher education.


Paper Information

Conference: ECE2025
Stream: Higher education

This paper is part of the ECE2025 Conference Proceedings (View)
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To cite this article:
Köse N., & Biçer �. (2025) Adapting the Student Attitudes Toward Artificial Intelligence (SATAI) Scale for Higher Education Contexts ISSN: 2188-1162 The European Conference on Education 2025: Official Conference Proceedings (pp. 647-660) https://doi.org/10.22492/issn.2188-1162.2025.51
To link to this article: https://doi.org/10.22492/issn.2188-1162.2025.51


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