LMS Acceptance Factors and Students’ Digital Learning Practices:

Abstract

Purpose: This research investigates whether Performance Expectancy, Effort Expectancy, and Facilitating Conditions are associated with Learning Experience and whether they have indirect associations with Digital Engagement and Digital Integration in Daily Life through that experience. Research Method: Survey responses from 114 university students who had used an LMS were examined with Partial Least Squares Structural Equation Modeling (PLS-SEM). Results and Discussion: Students reported better Learning Experience when they perceived stronger performance benefits and more adequate Facilitating Conditions. Effort Expectancy was not significantly associated with Learning Experience. Learning Experience, in turn, was positively related to Digital Engagement and Digital Integration in Daily Life. The indirect associations originating from Performance Expectancy and Facilitating Conditions were significant, whereas those originating from Effort Expectancy were not. Because Learning Experience and Digital Engagement showed only marginal empirical separation, findings involving these constructs require caution. The model did not include direct links from the acceptance factors to either outcome; consequently, the form of mediation cannot be determined. Implications: Universities can improve LMS-based learning by strengthening its educational value, ensuring access to support, and designing activities that students regard as meaningful. Future studies should use stronger measurement checks and longitudinal evidence. Originality: The study uses selected UTAUT2 constructs to investigate Learning Experience as an experiential bridge between students’ perceptions of an LMS and their subsequent digital learning practices.