Analyzing University Students’ Attitude and Behavior Toward AI Using the Extended Unified Theory of Acceptance and Use of Technology Model
Brandon Obenza, John Harry S Caballo, Ria Bianca R Caangay, Trisha Eunice C Makigod, Sharldawn M Almocera, John Lawrence M Bayno, Joseph Jr R Camposano, Sandy Jean G Cena, Judy Ann Kyll Garcia, Bea Faye M Labajo, Athena Grace Tua
Abstract
This quantitative study using Partial Least Square Structural Equation Modeling (PLS-SEM) examined a structural model of the attitudes and behaviors of university students toward AI in higher education. The results obtained using SmartPLS 4.0 indicate that the constructs exhibit validity and reliability (λ ≥ 0.708, α=0.767-0.948, AVE=0.584-0.777, HTMT=< 3.3). Further, the analysis of the hypothesized extended Unified Theory of Acceptance and Use (UTAUT) model reveals that AI Awareness significantly impacts Attitude toward AI (β = 0.156, p = 0.003) and Behavioral Intention to Use AI (BIU) (β = 0.337, p < 0.001). AI Trust also significantly influences Attitude toward AI (β = 0.366, p < 0.001) and BIU-AI (β = 0.173, p = 0.007). Additionally, Attitude toward AI is a strong predictor of BIU-AI (β = 0.457, p < 0.001). Social Influence significantly affects Attitude toward AI (β = 0.21, p < 0.001), while Effort Expectancy and Performance Expectancy do not show significant effects in this context. The link between Facilitating Conditions and BIU-AI is also insignificant. The model explained a substantial portion of the variance in attitude (R2 =0.612) and behavior (R2 =0.710). Fit indices indicate good model fit, and predictive relevance metrics were satisfactory.