British Journal of Educational Technology · 2011 · 755 citations · 32 references
EducationEducational TechnologyHigher EducationE-learningMobile ComputingPedagogyMobile LearningStructural Equation ModelingTechnology AdoptionIndividual AdoptionLearning OpportunitiesMobile Learning AdoptionTechnology AcceptanceTechnology Acceptance EvaluationTechnology Acceptance In LearningTechnology Adoption IntentionUser Adoption Intentions
Abstract As many Korean universities have recommended the implementation of mobile learning (m‐learning) for various reasons, the number of such tertiary learning opportunities has steadily grown. However, little research has investigated the factors affecting university students' adoption and use of m‐learning. A sample of 288 Konkuk university students participated in the research. The process by which students adopt m‐learning was explained using structural equation modeling technique and the Linear Structural Relationship (LISREL) program. The general structural model based on the technology acceptance model included m‐learning self‐efficacy, relevance for students' major (MR), system accessibility, subjective norm (SN), perceived usefulness, perceived ease of use, attitude (AT), and behavioral intention to use m‐learning. The study results confirmed the acceptability of the model to explain students' acceptance of m‐learning. M‐learning AT was the most important construct in explaining the causal process in the model, followed by students' MR and SN.
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Statistical Power Analysis for the Behavioral Sciences
Keith E. Muller, Jacob Cohen · Technometrics · 1989 · 83.9K citations
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh · MIS Quarterly · 2003 · 42.5K citations