TEACHERS' READINESS TO USE ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: PSYCHOLOGICAL AND INSTITUTIONAL CORRELATES

This study examines psychological and institutional factors associated with university teachers’ readiness to adopt artificial intelligence (AI) in teaching within social and humanitarian disciplines in a non-Western higher education context. A quantitative, cross-sectional correlational design was employed. Data were collected from 215 university teachers from four universities in Uzbekistan. Teachers’ readiness to adopt AI was examined in relation to perceived usefulness, perceived ease of use, digital self-efficacy, perceived institutional support, and ethical concerns. Pearson correlation analysis and hierarchical multiple regression were conducted while controlling for age, academic position, teaching experience, and prior experience with AI. Readiness to adopt AI was positively correlated with perceived usefulness (r = 0.48, p < .001), perceived ease of use (r = 0.34, p < .001), digital self-efficacy (r = 0.35, p < .001), and perceived institutional support (r = 0.44, p < .001), and negatively correlated with ethical concerns (r = −0.28, p < .001). In the final regression model, perceived usefulness (β = 0.32, p < .001), digital self-efficacy (β = 0.13, p = .038), and perceived institutional support (β = 0.21, p = .003) were significant positive predictors of readiness, whereas ethical concerns showed a significant negative association (β = −0.19, p < .001). Perceived ease of use was not significant in the full model. The model explained 36.8% of the variance in readiness. The findings indicate that teachers’ readiness to adopt AI is primarily associated with perceived pedagogical value, digital confidence, institutional support, and ethical considerations rather than demographic characteristics.