Acceptance of Smart Technologies in Blended Learning: Perspectives of Chinese Medical Students

Abstract

Smart technologies are essential in improving higher education teaching and learning. The present study explores the factors that influence students’ behavioural intentions to adopt and use smart technologies in blended learning. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, a survey of 305 students was conducted to collect data. A structural equation model was applied to analyse the data. The findings show that adopting smart technologies requires appropriate social context and organizational support. Moreover, the data indicated that performance expectancy, effort expectancy, social influence, hedonic motivation, and habit are vital in determining students’ behavioural intention to use smart technologies. However, facilitating conditions and price value were found to have no significant impact on the students’ behavioural intention to use smart technologies. The study contributes to a better understanding of the nexus of blended learning and smart technologies, thus improving students’ experiences in blended learning settings.