Predicting behavioral intention to use e-learning system: A case-study in Begum Rokeya University, Rangpur, Bangladesh.

Clicks: 217
ID: 275305
2022
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Digital transformation and emerging technologies open a horizon to a new method of teaching and learning and revolutionizes the e-learning industry. The goal of this study is to scrutinize a proposed research model for predicting factors that influence student's behavioral intention to use e-learning system at Begum Rokeya University, Bangladesh. The study used quantitative approach and developed a research model based on several technological acceptance models. In order to test the model, a survey was conducted to obtain data from 262 university students. SEM-PLS, a multivariate statistical analysis technique, was used to analyze the responses to examine the model, factors, structural relationships, and hypotheses. The result shows that 'perceived usefulness' and 'perceived ease of use' positively and significantly influenced by 'perceived enjoyment'. Furthermore, 'perceived usefulness', 'perceived ease of use' and 'facilitating condition' have a significant impact to predict behavioral intention to use e-learning. The results of mediation analysis show that 'perceived usefulness' and 'perceived ease of use' have mediating effects between the predictors and the outcome. Finally, 'facilitating condition' have a remarkable moderating effect to predict the student's behavioral intention in using e-learning. The findings have a noteworthy empirical implication for educational institutions to introduce e-learning system as one of the teaching and learning tools.
Reference Key
humida2022predictingeducation Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Humida, Thasnim;Al Mamun, Md Habib;Keikhosrokiani, Pantea;
Journal Education and information technologies
Year 2022
DOI
10.1007/s10639-021-10707-9
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.