Open AccessDeterminants of e-learning acceptance amongst Iranian postgraduate students
Author(s) -
Fatima Baji,
Fereydoun Azadeh,
Zivar Sabaghinejad,
Amir Zalpour
Publication year - 2022
Publication title -
journal of global education and research
Language(s) - English
Resource type - Journals
eISSN - 2577-509X
pISSN - 2577-5081
DOI - 10.5038/2577-509x.6.2.1089
Subject(s) - lisrel , technology acceptance model , psychology , structural equation modeling , e learning , medical education , validity , affect (linguistics) , predictive power , usability , mathematics education , educational technology , computer science , medicine , psychometrics , clinical psychology , philosophy , communication , epistemology , human–computer interaction , machine learning
E-learning can address some of the unmet needs of learners and educational communities; however, not all learners and educators accept e-learning as a delivery modality. This research endeavored to study the factors which affect e-learning acceptance among Iranian post-graduate students using the Davis Technology Acceptance Model (TAM) and to identify the changes which would facilitate their improved acceptance and subsequent wider use of e-learning. This descriptive-correlation study was conducted by surveying 320 Iranian postgraduate students using a self-reporting questionnaire. Structural equation modeling was used for data analysis through LISREL software. Results revealed sufficient validity and reliability of the TAM among Iranian postgraduate medical students. Perceived ease of use, perceived usefulness of e-learning, students’ attitudes toward e-learning, and the intention to use e-learning positively affected e-learning’s acceptance ( p < 0.05) among Iranian postgraduate students. According to the results, attitudes toward e-learning have more predictive power than other TAM constructs. Therefore, emphasis on students’ favorable attitudes toward e-learning can be effective in accelerating its acceptance and will progress students’ learning outcomes.