The DOI matches its Crossref record; 70 of the 72 references it cites were found in a registry or an index.
LMS-enabled blended learning utilization in distance tertiary education: establishing the relationships among facilitating conditions, voluntariness of use and use behaviour
Open accessAbstract
Abstract Distance education has evolved partly through technologies that defined them in the various generations of distance education delivery. However, in the twenty-first century, the use of Learning Management System (LMS) has changed the face of distance education delivery. Even the traditional face-to-face based distance education mode is now adopting the LMS as a mediating technology between instructors and students. However, in the usage of LMS-enabled blended learning, several factors have been cited in the literature as enablers towards actual usage of LMS technology. Factors such as facilitating conditions, voluntariness of use and actual use behaviour have been important in contemporary literature. Despite their importance, the chasm in the literature is the nuances existing in terms of relationships between these three factors. This study fills the gap by defining a model based on the three factors to provide an in depth empirical study on their relationships and how they influence LMS-enabled blended learning uptake of distance education by tutors. The study thus employs a cross country survey to collect data from 267 tutors and offer analysis by way of a Partial Least Squares Structural Equation Modelling (PLS-SEM) approach. The study revealed important relationships among facilitating conditions, voluntariness of use and use behaviour of LMS-enabled blended learning such that facilitating conditions predicted voluntariness of use and actual use behaviour; voluntariness of use determined actual LMS use behaviour for blended learning in distance education. The study finally provided recommendations based on the findings for policy and practice of LMS-enabled blended learning in distance education.
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“In the context of AR-assisted CBT, accessible devices, stable network conditions, appropriate usage environments, and timely technical support may reduce perceived barriers and improve students’ confidence in using the system [101,102].”
From Advancing Undergraduate Student Mental Healthcare of Social Anxiety Disorder: Evaluating the Acceptance of AR-Assisted Cognitive Behavioral Therapy Through TAM-Based Constructs. (2026) · cites this paper as [102]
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
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 · cited 9×
“Accordingly, we leverage on the views of Chiu and Ku (2015) and Venkatesh et al. (2003) to explain that the presence of enabling conditions such as internet availability, technological support, organizational/management support, motivation etc., has a propensity to enhance individuals ’…”
BackgroundMethodResultInfluentialA new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459 · cited 2×
“Henseler, Ringle, and Sarstedt (2015) recommend a higher assessment version of discriminant validity to be the Heterotrait-Monotrait-Ratio (HTMT).”
BackgroundInfluentialRogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
Designing and Conducting Mixed Methods Research
Robinson, P. M. (2007) · Australian and New Zealand Journal of Public Health · doi:10.1111/j.1753-6405.2007.00096.x · Cited by 23,362
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 20,559
Determining sample size for research activities
Krejcie, R. V., & Morgan, D. W. (1970) · Educational and Psychological Measurement · doi:10.1177/001316447003000308 · Cited by 18,930 · cited 1×
“According to Krejcie and Morgan (1970), the minimum sample size for a population of 400 is about 196 respondents.”
BackgroundVenkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756 · cited 1×
“Items were modified from Venkatesh et al. (2003) and Venkatesh et al. (2012).”
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150 · cited 1×
“Voluntariness of Use is defined as “ the degree to which use of the innovation is perceived as being voluntary, or of free will ” (Moore & Benbasat, 1991, p. 195; Ramayah, 2010).”
Background
Research works printed but not linked: 7
- Adkins, S. S. (2013). The Africa market for self-paced eLearning products and services: 2011-2016 forecast and analysis Available at: http://www.ambientinsight.com/Resources/Documents/AmbientInsight-2011-2016-Africa-SelfPaced-eLearningMark-et-Abstract.pdf.
- Africa American Institute (2015). A report card on the progress, opportunities and challenges confronting the African education sector State of Education in Africa Report 2015.
- Ellis, R. K. (2009). Field guide to learning management systems, ASTD learning circuitsRetrieved 7th June, 2017 from http://www.astd.org/~/media/Files/Publications/LMS_fieldguide_20091.pdf.
- Kline, R. B. (2015). Principles and practice of structural equation modelling methodology in the social sciences, (4th ed., ). New York: Guilford Publication.
- Martin, J. (2009). Developing course material for online instruction of adults. Journal of Online Learning and Teaching, 5(2), 364.
- Oakes, K. (2002). E-learning: LCMS, LMS- They’re not just acronyms but powerful systems for learning. Training & Development, 56(3), 73–75.
- Sharma, A., & Vatta, S. (2013). Role of learning management systems in education. International Journal of Advanced Research in Computer Science and Software Engineering, 3(6), 997-1002.
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Xue, L., Rashid, A. M., & Ouyang, S. (2024) · SAGE Open · doi:10.1177/21582440241229570 · Cited by 465
Baig, M. I., & Yadegaridehkordi, E. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00506-4 · Cited by 161
Tecnologías avanzadas para afrontar el reto de la innovación educativa
Espinosa, M. P. P., & Cerdán, F. (2020) · RIED Revista Iberoamericana de Educación a Distancia · doi:10.5944/ried.24.1.28415 · Cited by 145
Breiki, M. A., Al-Abri, A., Moosawi, A. M. S. A., & Buraiki, A. A. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11367-z · Cited by 75
“Bervell & Arkorful (2020) SN2: My science senior teachers would prefer that I adopt virtual reality in my teaching.”
BackgroundInfluentialSegbenya, M., Bervell, B., Minadzi, V. M., & Somuah, B. A. (2022) · Smart Learning Environments · doi:10.1186/s40561-022-00193-y · Cited by 63
“How each construct found in the model differ from other constructs was determined by using the Heterotrait-Monotrait Ratio (HTMT) based on the suggested criterion of Henseler et al. (2015) cited in Bervell and Arkorful (2020).”
MethodInfluential
Metadata
- Authors
- Bervell, B., & Arkorful, V.
- Affiliations
- University of Cape Coast (GH)
- Corresponding author
- Bervell, Brandford
- Venue
- International Journal of Educational Technology in Higher Education
- Published
- 2020-03-17
- Volume
- 17
- Issue
- 1
- ISSN
- 2365-9440 (ISSN-L)
- OpenAlex
- W3015007848
- Cited by
- 144
- References
- 72
- Citations by year
- 2026: 11 · 2025: 23 · 2024: 24 · 2023: 22 · 2022: 29 · 2021: 28 · 2020: 7
- FWCI
- 32.58
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- International Journal of Educational Technology in Higher Education (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Greater South Information System
- Funders
- University of Cape Coast (TDS/109/V.2/97)
- Topics
- Social Sciences › Education › Online and Blended Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- virtual learning environments, blended learning, distance education, facilitating conditions, tutors, technology adoption, higher education
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