Factors driving the adoption of m-learning: An empirical study

Abstract

Even if m-learning is spreading rapidly in many regions of the world, research addressing the driving factors of m-learning adoption is in short supply. Built on the Technology Acceptance Model, this paper proposes a hypothesized model of m-learning adoption. Employing structural equation modeling technology, the model was assessed based on the data collected from 230 participants using a survey questionnaire. Results indicate that perceived near-term/long-term usefulness and personal innovativeness have significant influence on m-learning adoption intention, while perceived long-term usefulness significantly affects the perceived near-term usefulness. Personal innovativeness is a predictor of both the perceived ease of use and perceived long-term usefulness as well. Of all variables, the perceived long-term usefulness contributes to the most influential predictor of m-learning adoption. The model accounts for approximately 60.8% of the variance of behavioural intention. The results indicted that offing high-quality contents complying with students’ future targets is key to the success of m-learning in China. Both theoretical and practical implications are discussed.