Dataset on technology acceptance in E-learning: A PLS-SEM analysis using extended TAM among undergraduate students in Indonesia

Abstract

The data set, and analysis presented in this study is about the factors that affect the adoption of e-learning by undergraduate students in Indonesia using an extended Technology Acceptance Model. The traditional TAM constructs, perceived usefulness and perceived ease of use, are extended to include enjoyment, perceived risk, perceived compatibility, and perceived self-efficacy for deeper insight into students' acceptance of e-learning technologies. A structured survey was undertaken for data collection from 645 students at Pelita Bangsa University. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data. Results confirm that extended TAM constructs improve students' acceptance and use of e-learning. Perceived Enjoyment and Self-Efficacy emerged as strong predictors of variance in adopting e-learning, while Perceived Risk moderated some relationships. Therefore, The findings and analysis provide valuable lessons for educators and policymakers seeking to advance e-learning platforms to increase higher education adoption rates. The findings imply several important practical implications for creating a more effective e-learning system to meet student preferences and minimize perceived barriers.

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