AI-assisted learning applications in English courses in Vietnam

Abstract

This paper investigates the factors influencing students’ intention to use AI-assisted learning applications in English courses through the Uses and Gratification Theory lens. Utilizing a sample of English course participants, we hypothesize that social, process, content, and technology gratifications derived from using AI learning apps positively impact perceived enjoyment levels, which in turn influence students’ intention to use these applications. The research model integrates these constructs, proposing direct relationships between gratifications and perceived enjoyment and an impact of perceived enjoyment on the intention to use. Data analysis, employing structural equation modeling techniques, reveals significant positive effects of social, process, content, and technology gratifications on perceived enjoyment, supporting our hypotheses. Moreover, perceived enjoyment emerges as a significant predictor of intention to use AI learning apps. These findings contribute to understanding user motivations and behaviors in adopting AI technologies for educational purposes, offering implications for educators, developers, and policymakers aiming to enhance English language learning experiences through AI-assisted platforms.