Psychometric Properties Analysis of the Artificial Intelligence Self-Efficacy Scale for University Students in Indonesian
DOI:
https://doi.org/10.24843/JPU.2026.v13.i01.p02Keywords:
Artificial Intelligence, Psychometric, Self-EfficacyAbstract
This study aims to analyze the psychometric properties of the Indonesian version of the Artificial Intelligence Self-Efficacy Scale (AISES) among university students. The adaptation refers to the International Test Commission (2017) guidelines, and content validity is analyzed using Aiken's V method to ensure conceptual and semantic appropriateness. This study involved 560 students in Indonesia as subjects, with sample selection using non-probability sampling techniques in the form of purposive sampling. This study successfully confirmed the internal structure of AISES using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), which consisted of four dimensions, namely Assistance, Anthropomorphic Interaction, Comfort with AI, and Technological Skills with a good model fit index (CFI = 0.914, TLI = 0.902, RMSEA = 0.061, SRMR = 0.063). Despite removing one item in the Technological Skills dimension, the Indonesian version of AISES has a fairly high reliability coefficient with Cronbach's α = 0.908 and McDonald's ω = 0.916. The results show that the Indonesian version of AISES is a valid and adequate instrument for measuring self-efficacy towards AI in the student population.
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