DEVELOPMENT OF THE EDUCATIONAL ARTIFICIAL INTELLIGENCE USE CONCERNS SCALE
Abstract
The rapid proliferation of artificial intelligence (AI) tools in higher education has brought pedagogical opportunities to the fore, but it has also made students’ affective responses, particularly concern related to AI usage, more visible. The aim of this study is to develop the Educational Artificial Intelligence Use Concerns Scale within the framework of the Technology Acceptance Model (TAM) and AI concern and anxiety literature. The scale development process was conducted using the classical test theory approach and included the following stages: item pool creation, content validity through expert opinion, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability-validity analyses. Data were collected from higher education students enrolled at [name of university / universities] in [city, country] through an online survey distributed via [institutional e-mail / classroom announcements / learning management system / social media], and separate samples were used for EFA (n = 300) and CFA (n = 129). CFA results yielded a two-factor structure, explaining 57.99% of the total variance. CFA findings revealed that the twofactor structure showed acceptable/excellent fit (χ²/df=1.88; CFI=.98; TLI=.98; RMSEA=.08; SRMR=.01). The scale’s internal consistency was found to be high (total α = .90), and convergent validity was supported by AVE values. The results indicate that the scale is a valid and reliable tool for measuring concerns related to AI use in higher education contexts. The scale can contribute to studies explaining the acceptance and integration of AI in education, particularly when used in conjunction with TAM variables, by examining the role of affective determinants in technology acceptance processes.
Keywords
Artificial intelligence, concern, scale development, higher education, technology acceptance model
Ethical Statement
Thanks
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