Understanding AI and Mobile Learning Adoption in Malaysian Universities: A UTAUT-Based Model

Abstract

This study explores the key determinants influencing the intention to adopt artificial intelligence (AI) applications and mobile learning in Higher Education Institutions (HEIs) in Malaysia. As AI technologies and mobile learning increasingly transform the higher education landscape, it is crucial to understand the specific factors driving their adoption. The research identifies five critical determinants—social influence (SI), effort expectancy (EE), hedonic motivations (HM), performance expectancy (PE), and consumer trust (TR)—that significantly impact the intention to use AI-powered mobile learning solutions. Through a survey of 263 undergraduate and postgraduate students from Malaysian universities, the study develops an adapted model to assess these adoption factors, contributing unique insights into the integration of AI and mobile learning within the Malaysian higher education context. This model provides actionable recommendations for university administrators, educators, and mobile learning developers, offering practical guidance on promoting the adoption of these technologies to enhance student engagement and learning outcomes. By focusing on real-world application, this study not only bridges theoretical research with practical implementation but also offers valuable lessons for similar educational contexts globally, particularly in emerging markets.