Online Information Review · 2022 · 11 citations · 73 references
EducationEducational TechnologyHigher EducationE-learningPedagogyStudent EngagementMobile LearningTechnology AdoptionTechnology IntegrationMobile Learning AdoptionMobile Media UseQuantitative Data CollectionTechnology Acceptance In Learning
Purpose In parallel with technological developments, mobile devices have become an important part of our daily lives. Nowadays, people, particularly generation Z, actively engage with the Internet and mobile technologies, including smartphones. The new technologies have also made electronic learning (e-learning) and mobile learning (m-learning) tempting for learners in higher education. Despite the growing use of m-learning, particularly in developed countries, its utilization in higher education is still at its early stage and far from its potential. This study investigates the university students' acceptance of using m-learning with smartphones in a developing country context. Design/methodology/approach Quantitative data collected through conducting questionnaires with 405 higher education students in Turkey were analyzed with structural equation modelling. Findings The findings show that the acceptance of using m-learning is affected by several factors, including perceived enjoyment, complexity and facilitating conditions. The findings are particularly relevant in the current context, where the COVID-19 pandemic has pushed many higher education institutions to adapt m-learning systems to enhance student learning experiences. Originality/value This study's findings offer fresh and important insights that can be used by m-learning developers and educators for designing m-learning systems and using m-learning applications in enhancing students' experience and performance with m-learning. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0516 .
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User Acceptance of Information Technology: Toward A Unified View1
Venkatesh · MIS Quarterly · 2003 · 42.5K citations
The partial least squares approach for structural equation modeling.
Wynne W. Chin · 1998 · 11.7K citations