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Cited by 133Technology Adoption and User BehaviourTechnology-Enhanced Education StudiesOnline and Blended Learning

The DOI matches its Crossref record; 57 of the 59 references it cites were found in a registry or an index.

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

Open access
Humida, Thasnim, Al Mamun, Md Habib, Keikhosrokiani, Pantea·2022·Education and Information Technologies
DOI 10.1007/s10639-021-10707-9PMC PMC8364304
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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.

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  1. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2018). Multivariate Data Analysis (8th ed.). Cengage Learning EMEA.

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Metadata

Authors
Humida, T., Al Mamun, M. H., & Keikhosrokiani, P.
Affiliations
  • Begum Rokeya University (BD)
  • Universiti Sains Malaysia (MY)
Corresponding author
  • Humida, Thasnim
  • Keikhosrokiani, Pantea
ORCID
Keikhosrokiani, Pantea
Venue
Education and Information Technologies
Publisher
Springer Science and Business Media LLC
Published
2021-08-14
Volume
27
Issue
2
Pages
2241-2265
ISSN
  • 1360-2357 (ISSN-L)
  • 1573-7608
DOI
10.1007/s10639-021-10707-9
PMC
PMC8364304
OpenAlex
W3195725675
Cited by
133
References
59
Citations by year
2026: 15 · 2025: 35 · 2024: 37 · 2023: 28 · 2022: 17 · 2021: 1
FWCI
17.70
Type
journal article
Language
en
Open access
Licence
Locations
  • Education and Information Technologies (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
Universiti Sains Malaysia (304/PKOMP/6315435)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Education › Technology-Enhanced Education Studies
  • Social Sciences › Education › Online and Blended Learning
Keywords
e-learning adoption, behavioral intention, university students, perceived usefulness, perceived ease of use, perceived enjoyment, facilitating conditions, technology acceptance model, digitalization of education

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