Extending UTAUT2 toward acceptance of mobile learning in the context of higher education

Author Affiliation

Wajid H. Rizvi is Assistant Professor and Chairperson Marketing Department at Institute of Business Administration (IBA), Karachi

Faculty / School

Faculty of Computer Sciences (FCS)

Department

Department of Marketing

Was this content written or created while at IBA?

Yes

Document Type

Article

Source Publication

Universal Access in the Information Society

ISSN

1615-5289

Disciplines

Computer Sciences | Databases and Information Systems | Graphics and Human Computer Interfaces | Software Engineering

Abstract

The use of smartphones as a learning tool in education is on the rise, causing a rapidly developing use of mobile learning (m-learning) in both developed and developing countries. The key features of smartphones, i.e., mobility, ubiquity, lightweight, low-cost and connectivity from anywhere and anytime, enhance their usage in a variety of ways. M-learning is an innovative idea that provides enormous opportunities by connecting humans and technology, such as better learning experiences and technology acceptance. The use of m-learning is growing at a higher pace worldwide, yet sufficient understanding of the factors that influence its acceptance in society is still lacking, particularly in developing countries. A number of models related to m-learning acceptance do exist, for instance, the extended unified theory of acceptance and use of technology (UTAUT2); however, the use of UTAUT2 to study m-learning acceptance is scant in the context of higher education institutes and it does not cover specific features of mobile devices. Therefore, this study not only uses UTAUT2 as a base theoretical framework but also extends it using five other constructs: ubiquity, information quality, system quality, appearance quality and satisfaction. A cross-sectional survey was conducted in two engineering universities in Pakistan. The questionnaire was administered among 900 students, out of which 730 usable responses were selected for further analysis. The data were analyzed using structural equation modeling. The findings revealed that the model fits data well; the model fit indices were within the recommended thresholds. The performance expectancy, hedonic motivation, habit, ubiquity and satisfaction have statistically significant impact on the behavioral intention and the information quality, system quality and appearance quality also have statistically significant impact on the mediator satisfaction toward m-learning acceptance. This study contributes to the body of literature related to technology acceptance models for m-learning by making a tailored extension in UTAUT2 that provides valuable insights into assess m-learning acceptance in the context of higher education institutes of developing countries, specifically in Pakistan.

Indexing Information

HJRS - W Category, Scopus, Web of Science - Science Citation Index Expanded (SCI), Web of Science - Social Sciences Citation Index (SSCI)

Publication Status

Published

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