Factors influencing students’ acceptance of m-learning: An investigation in higher education

By Ahmad Abu-Al-Aish, Steve Love. 2013

360 citations recorded by the source corpus.

M-learning will play an increasingly significant role in the development of teaching and learning methods for higher education. However, the successful implementation of m-learning in higher education will be based on users’ acceptance of this technology. Thus, the purpose of this paper is to study the factors that affect university students’ intentions to accept m-learning. Based on the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors that influence the acceptance of m-learning in higher education and to investigate if prior experience of mobile devices affects the acceptance of m-learning. A structural equation model was used to analyse the data collected from 174 participants. The results indicate that performance expectancy, effort expectancy, influence of lecturers, quality of service, and personal innovativeness were all significant factors that affect behavioural intention to use m-learning. Prior experience of mobile devices was also found to moderate the effect of these constructs on behavioural intention. The results of this research extend the UTAUT in the context of m-learning acceptance by adding quality of service and personal innovativeness to the structure of UTAUT and provide practitioners and educators with useful guidelines for designing a successful m-learning system.

Subfields: Information Systems, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/8903306a169e722681b8dbb5001cb3db414ccd2f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

In Information Systems and Management

In Sociology and Political Science

Citations in the corpus

Investigating attitudes towards the use of mobile learning in higher education (2016, background): “Abu-Al-Aish and Love (2013) proposed a model that identifies the factors influencing the acceptance of M-learning in higher education based on the unified theory of acceptance and use of technology (UTAUT) concluding that performance expectancy, effort expectancy, lecturers' influence, quality of…”
Habit and hedonic motivation are the strongest influences in mobile learning behaviours among higher education students in Malaysia (2019, background): “In the context of mobile learning, students may believe that the learning system is beneficial as it enhances their work performance and learning productivity (Abu-Al-Aish & Love, 2013), apart from allowing them to acquire knowledge conveniently and rapidly (Jackman, 2014).”
Mobile-based assessment: Investigating the factors that influence behavioral intention to use (2017, background): “The same relationships among these variables exist for mobile learning (Abu-Al-Aish & Love, 2013; Briz-Ponce et al., 2016; Mac Callum, Jeffrey, & Kinshuk, 2014; Park et al., 2012) and computer-based assessment acceptance as well (Terzis & Economides, 2011).”