Psychometric properties and factorial structure of the AI tools adoption scale in scientific research: a study of graduate students in special education departments in Saudi Arabia

Abstract This study aimed to examine the psychometric properties and factorial structure of the AI Tools Adoption Scale in scientific research among graduate students in special education departments in Saudi Arabia. A descriptive-structural methodology was employed with a sample of 418 graduate students from six Saudi public universities. Exploratory and confirmatory factor analyses were conducted on independent random subsamples (n₁ = n₂ = 209) to identify and cross-validate the underlying structure of the developed 42-item scale. Exploratory Factor Analysis results revealed six latent factors collectively explaining 55.46% of the total item variance: Perceived Usefulness, Perceived Ease of Use, Technology Self-Efficacy, Anxiety and Perceived Risks, Facilitating Conditions and Institutional Support, and Academic Integrity and Ethical Risks. Goodness-of-fit indices demonstrated excellent values ( CFI  = 0.93, TLI  = 0.93, RMSEA  = 0.04), with composite reliability coefficients ranging from 0.71 to 0.79 and Cronbach’s alpha coefficients between 0.74 and 0.88. Findings confirmed that the scale possesses robust psychometric properties, making it a valid and reliable instrument for use in Saudi public universities with graduate Special Education programs.