Students’ e-learning acceptance
Empirical evidence from higher learning institutions
Bibliographic Data
| ID | 12428258 |
|---|---|
| Authors | Imran Mehboob Shaikh (0000-0001-5552-693X, Universiti of Malaysia Sabah, corresponding author), Geoffrey Harvey Tanakinjal (0000-0002-7057-2851, Universiti of Malaysia Sabah), Hanudin Amin (0000-0003-3645-287X, Universiti of Malaysia Sabah), Kamaruzaman Noordin (0000-0002-5844-6035, University of Malaya), Junaid Shaikh (University of South Australia) |
| Year | 2024 |
| Volume | 33 |
| Issue | 1 |
| Pages | 1-13 |
| Publication date | 2024-06-28 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | On the Horizon The International Journal of Learning Futures (JOURNAL) |
| Journal identifiers | ISSN: 1074-8121 • E-ISSN: 2054-1708 |
| Publisher | Emerald Publishing Limited (PUBLISHER • GB) |
| DOI | 10.1108/oth-08-2022-0041 |
| OpenAlex | W4400136260 |
| Language | EN |
| References cited | 24 |
Purpose The purpose of this paper is to investigate the factors that influence business students’ adoption of e-learning systems by merging innovation diffusion theory (IDT) and the teaching for professional competence model (TPCM). Design/methodology/approach Snowball sampling was used to conduct the survey. In addition, 217 responses were obtained from students at private educational institutions. Similarly, literature on the determinants of e-learning adoption, TPCM, and IDT were reviewed to contribute to the factors that are instrumental in determining e-learning systems adoption. Findings The findings of the study show that e-learning systems adoption is influenced by factors such as online collaborative learning (OCL) and technology self-efficacy. Above all, the OCL variable was found to be influential in determining students’ adoption of e-learning systems platforms. On the contrary, perceived attributes such as perceived compatibility and perceived relative advantage were found not to be significant determinants of e-learning systems adoption. Research limitations/implications This study contributed not only to the theoretical extensions but also to practical implications, which would benefit the policymakers of higher education providers in terms of e-learning system adoption in the country. Originality/value IDT and TPCM models are evaluated alongside additional variables, namely, OCL and technology self-efficacy. As a result, this paper will serve as a useful reference guide for academicians, higher education administrators, and future researchers
Competence (human resources · Creativity · Higher education · Knowledge management · Mathematics education · Originality · Political science · Snowball sampling · Computer Science · Digital Marketing and Social Media · Knowledge Management and Sharing · Mathematics · Psychology · Social Psychology · Technology Adoption and User Behaviour
Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation
Knowledge-Sharing Dilemmas
A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects
Self-Efficacy for Reading and Writing
Self-Efficacy and Academic Motivation
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
PLS-SEM or CB-SEM
E-learning challenge studying the Covid-19 pandemic
The use of a decomposed theory of planned behavior to study Internet banking in Taiwan
| Citation velocity | historical |
|---|---|
| Highly cited | No |