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Predicting behavioral intention to use e-learning system: A case-study in Begum Rokeya University, Rangpur, Bangladesh
Open accessAbstract
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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“This is a significant theoretical advance over earlier ISSM and TTF investigations, which did not examine the impact of perceived usability, perceived usefulness, system use, and task-technology fit on the applied ethical aim [85,107,108].”
From Acceptance of e-learning in higher education: the role of task-technology fit with the information systems success model (2023) · cites this paper as [107]
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“Empirical research consistently demonstrates PU's direct positive influence on behavioral intention (BI).”
From From Perception to Practice: Artificial Intelligence as a Pathway to Enhancing Digital Literacy in Higher Education Teaching (2025) · cites this paper as [25]
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Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
(1980) · Medical Entomology and Zoology · Cited by 25,810
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1978) · Advances in Behaviour Research and Therapy · doi:10.1016/0146-6402(78)90002-4 · Cited by 10,586
Understanding information technology usage: a test of competing models
Taylor, S., & Todd, P. A. (1995) · Information Systems Research · doi:10.1287/isre.6.2.144 · Cited by 8,815
Extrinsic and Intrinsic Motivation to Use Computers in the Workplace 1
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1992.tb00945.x · Cited by 6,231
Agarwal, R., & Karahanna, E. (2000) · MIS Quarterly · doi:10.2307/3250951 · Cited by 4,726
Extending the TAM for a World-Wide-Web context
Moon, J.-W., & Kim, Y.-G. (2001) · Information & Management · doi:10.1016/s0378-7206(00)00061-6 · Cited by 3,802
Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior
Koufaris, M. (2002) · Information Systems Research · doi:10.1287/isre.13.2.205.83 · Cited by 3,240
Deci, E. L. (1975) · doi:10.1007/978-1-4613-4446-9 · Cited by 2,911
Venkatesh, V., & Morris, M. G. (2000) · MIS Quarterly · doi:10.2307/3250981 · Cited by 2,780
Research methods for business : a skill-building approach 6th ed.
Sekaran, U., & Bougie, R. (2013) · Cited by 2,456
Belief, attitude, intention, and behavior: An introduction to theory and research
Hill, R. J., Fishbein, M., & Ajzen, I. (1977) · Contemporary Sociology · doi:10.2307/2065853 · Cited by 2,379
Self-efficacy: Toward a unifying theory of behavioural change?
Teasdale, J. D. (1978) · Advances in Behaviour Research and Therapy · doi:10.1016/0146-6402(78)90009-7 · Cited by 2,038
Schepers, J., & Wetzels, M. G. M. (2006) · Information & Management · doi:10.1016/j.im.2006.10.007 · Cited by 1,808
Factors influencing the usage of websites: the case of a generic portal in The Netherlands
van der Heijden, H. (2003) · Information & Management · doi:10.1016/s0378-7206(02)00079-4 · Cited by 1,465
The effects of self-efficacy on computer usage
Igbaria, M. (1995) · Omega · doi:10.1016/0305-0483(95)00035-6 · Cited by 1,064
Critical success factors for e-learning acceptance: Confirmatory factor models
Selim, H. M. (2007) · Computers & Education · doi:10.1016/j.compedu.2005.09.004 · Cited by 1,055
Hinton, P. R., McMurray, I., & Brownlow, C. (2014) · Routledge eBooks · doi:10.4324/9781315797298 · Cited by 1,025
Abdullah, F., & Ward, R. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.11.036 · Cited by 986 · cited 9×
“Abdullah et al. discovered Self-Efficacy (SE) as the most usual external factor used in the TAM model (Abdullah & Ward, 2016; Keikhosrokiani, 2019; Keikhosrokiani et al., 2019).”
BackgroundMethodInfluentialUser Acceptance Enablers in Individual Decision Making About Technology: Toward an Integrated Model
Venkatesh, V., Speier, C., & Morris, M. G. (2002) · Decision Sciences · doi:10.1111/j.1540-5915.2002.tb01646.x · Cited by 948
Baptista, G., & Oliveira, T. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.04.024 · Cited by 922
Assessing computer anxiety: Development and validation of the Computer Anxiety Rating Scale
HEINSSEN, R. K., Glass, C. R., & Knight, L. A. (1987) · Computers in Human Behavior · doi:10.1016/0747-5632(87)90010-0 · Cited by 806
Abdullah, F., Ward, R., & Ahmed, E. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.014 · Cited by 693
Al-Gahtani, S. S., & King, M. (1999) · Behaviour & Information Technology · doi:10.1080/014492999119020 · Cited by 519
Igbaria, M., & Parasuraman, S. (1989) · Journal of Management · doi:10.1177/014920638901500302 · Cited by 485
Learning with mobile technologies – Students’ behavior
Briz-Ponce, L., Pereira, A., Carvalho, L., Méndez, J. A. J., & García‐Peñalvo, F. J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.027 · Cited by 430
Mobile-based assessment: Investigating the factors that influence behavioral intention to use
Nikou, S. A., & Economides, A. A. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.02.005 · Cited by 388
Hamidi, H., & Chavoshi, A. (2018) · Telematics and Informatics · doi:10.1016/j.tele.2017.09.016 · Cited by 374
Technology Acceptance Model and E-learning
Masrom, M. B., & Teknologi, U. (2007) · Cited by 363
Adoption of e-government services in Turkey
Kurfalı, M., Arifoğlu, A., Tokdemir, G., & Paçin, Y. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.09.041 · Cited by 342
An investigation of employees' use of e-learning systems: applying the technology acceptance model
Lee, Y., Hsieh, Y. G., & Chen, Y. (2011) · Behaviour and Information Technology · doi:10.1080/0144929x.2011.577190 · Cited by 259
A model of organizational employees’ e-learning systems acceptance
Lee, Y., Hsieh, Y. G., & Ma, C.-Y. (2010) · Knowledge-Based Systems · doi:10.1016/j.knosys.2010.09.005 · Cited by 181
Determining the factors influencing students’ intention to use m-learning in Jordan higher education
Althunibat, A. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.05.046 · Cited by 179
E-learning system use and its outcomes: Moderating role of perceived compatibility
Islam, A. K. M. N. (2015) · Telematics and Informatics · doi:10.1016/j.tele.2015.06.010 · Cited by 172
Smet, C. D., Bourgonjon, J., Wever, B. D., Schellens, T., & Valcke, M. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.09.013 · Cited by 172
Wang, T., Lin, C., & Su, Y.-S. (2021) · Sustainability · doi:10.3390/su13084586 · Cited by 158
Understanding the role of user resistance on mobile learning usage among university students
Kim, H., Lee, J.-M., & Rha, J. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.05.015 · Cited by 140
E‐learning in small organisations
Sambrook, S. A. (2003) · Education + Training · doi:10.1108/00400910310508892 · Cited by 128
Adapting to changing expectations: Post-graduate students’ experience of an e-learning tax program
Engelbrecht, E. (2004) · Computers & Education · doi:10.1016/j.compedu.2004.08.001 · Cited by 118
Qiao, P., Zhu, X., Guo, Y., Sun, Y., & Qin, C. L. (2021) · Journal of risk and financial management · doi:10.3390/jrfm14040162 · Cited by 113
Keikhosrokiani, P., Mustaffa, N., Zakaria, N., & Abdullah, R. (2019) · Cognition Technology & Work · doi:10.1007/s10111-019-00565-4 · Cited by 67
Self-citationSuccess factors in developing iHeart as a patient-centric healthcare system: A multi-group analysis
Keikhosrokiani, P., Mustaffa, N., & Zakaria, N. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2017.11.006 · Cited by 66
Self-citationEvaluating a model of business school students' acceptance of web-based course management systems
Williams, M., & Williams, J. (2010) · The International Journal of Management Education · doi:10.3794/ijme.83.264 · Cited by 37
User Behavioral Intention Toward Using Mobile Healthcare System
Keikhosrokiani, P., Mustaffa, N., Zakaria, N., & Baharudin, A. S. (2018) · IGI Global eBooks · doi:10.4018/978-1-5225-6198-9.ch022 · Cited by 24
Self-citationA model of user acceptance of E-learning technologies: A case study of a polytechnic in New Zealand
Nanayakkara, C., & Whiddett, R. (2005) · Cited by 22
Behavioral intention to use of Mobile Medical Information System (mMIS)
Keikhosrokiani, P. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-817657-3.00004-3 · Cited by 12
Self-citationPerspectives in the Development of Mobile Medical Information Systems
(2019) · Elsevier eBooks · doi:10.1016/c2018-0-02485-8 · Cited by 10
The Role of m-Commerce Literacy on the Attitude towards Using e-Torch in Penang, Malaysia
Keikhosrokiani, P. (2021) · Intelligent information systems · doi:10.1142/9789811231841_0013 · Cited by 9
Self-citation
Research works printed but not linked: 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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“It is claimed that PE significantly influences users’ intentions to adopt hedonic systems or technologies such as metaverse, as being ones which give users joy or pleasure (Humida et al., 2022; Van der Heijden, 2004 ).”
BackgroundXue, L., Rashid, A. M., & Ouyang, S. (2024) · SAGE Open · doi:10.1177/21582440241229570 · Cited by 465
Alyoussef, I. Y. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e13751 · Cited by 181
Shi, Y., Siddik, A. B., Masukujjaman, M., Zheng, G.-W., Hamayun, M., & Ibrahim, A. M. (2022) · Sustainability · doi:10.3390/su14116640 · Cited by 141
Qu, K., & Wu, X. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12598-y · Cited by 164
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
- Venue
- Education and Information Technologies
- Published
- 2021-08-14
- Volume
- 27
- Issue
- 2
- Pages
- 2241-2265
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- 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
- bronze
- doi.org
- 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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