Determinants of Autonomous AI Use in Multilingual English Learning at Pakistani Universities: A UTAUT Study

Abstract

This article investigates the push factors to make teachers and students use AI tools independently in Pakistani tertiary education, in multilingual English classrooms, without any obligation by the institution. Based on the UTAUT model, we collected a data set from 213 subjects and adopted structural equation modeling to analyze the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, and actual use. Findings suggest that students closely associate ease of use with perceived usefulness, whereas teacher attitude as a whole predicts actual AI usage. The model was a reasonably good fit to the data. We propose the development of pragmatic AI competency guides that will guarantee fair access for all learners, regardless of language and economic status, towards a set of sensible context-aware policies that bring us closer to responsible and effective use of AI in English teaching and learning.