Extended Unified Theory of Acceptance and Use of Technology in Mobile Learning: A Systematic Review

Abstract

Technology acceptance, as a prerequisite for the successful implementation of mobile learning, has received much academic effort based on different theories. As a comprehensive theory in exploring individual technology acceptance, the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) has gained increasing attention in information systems and beyond. Nevertheless, there is a gap in existing knowledge regarding literature that systematically synthesizes research on UTAUT2 in an educational context. Given this, the present study was conducted to comprehensively review existing studies on the acceptance of mobile learning (m-learning) so as to get a clear and in-depth understanding of learners’ needs and preferences. We searched studies that empirically examined m-learning acceptance based on UTAUT2 from four databases in October 2020. Following the guidelines in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, 20 studies were identified and included. The results highlighted the current research trend of previous studies in terms of year of publication, distribution of country and journal, type of technology, and research method. Besides, the determinants of the acceptance of m-learning were identified. The main findings include that hedonic motivation was the most validated predictor of users’ behavioural intention, followed by performance expectancy, habit and social influence, while effort expectancy, facilitating conditions and price value were reported to be nonsignificant in more than half of the studies reviewed. Most studies applied a part of UTAUT2 in a particular research context, but a few studies extended the model with external variables such as trust, technological innovativeness, and personal innovativeness. The findings also reveal that the investigation of moderating effects was lacking in the existing literature. Most studies were undertaken in developing countries in Asia in the context of higher education and self-reported questionnaire surveys were the single method of data collection used in all studies with the partial least squares structural equation modeling (PLS-SEM) being the most frequently adopted data analysis method. Further efforts can be dedicated to extending UTAUT2 with external variables to tailor to the m-learning context and to further examine the effect of moderating variables. A great diversity of respondents is also encouraged in future studies so that deeper insights can be gained from students and teachers at different educational stages. Furthermore, longitudinal studies are needed to explore technology acceptance at various phases such as adoption, initial use, or post-adoptive use.