Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education

Brandford Bervell; Irfan Naufal Umar; Mona Masood; Jeya Amantha Kumar; Justice Kofi Armah; Beatrice Asante Somuah

doi:10.30935/cedtech/12193

Brandford Bervell ¹ ² ^* , Irfan Naufal Umar ², Mona Masood ², Jeya Amantha Kumar ², Justice Kofi Armah ¹, Beatrice Asante Somuah ³

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CONT ED TECHNOLOGY, Volume 14, Issue 4, Article No: ep379

https://doi.org/10.30935/cedtech/12193

Submitted: 23 February 2022, Published Online: 29 June 2022

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Abstract

Contemporary distance higher education is hinged on modern technologies to deliver purely online and blended modes of learning mostly through learning management system (LMS). This is to bridge the transactional gap between students and instructors as well as among students themselves. However, the use of technologies such as LMS for dispensing distance tertiary education is at a cross-road of mandatoriness or voluntariness of use. Nonetheless, current literature supports the voluntary use of LMS by instructors in order to foster positive attitudes and personalization among instructors. Based on this, there is the need to unravel the determining facts that promote voluntary usage of LMS among tutors.
This study thus, employs a quantitative approach based on a survey design to purposively collect data from 267 tutors in a blended distance education setting using a questionnaire. Generalized structural component analysis technique was adopted for structural equation modelling. Results from a structural equation modelling revealed that performance expectancy, effort expectancy, facilitating conditions, and social influence, all determine tutors’ voluntariness of use of LMS for blended learning in distance education. Additionally, voluntariness of use predicted actual LMS use behavior among tutors. On the basis of the results, recommendations were made to reflect theory, policy and practice of voluntary integration of LMS by tutors for blended learning in distance education.

Keywords: LMS, voluntariness of use, tutors, blended learning, distance higher education, generalized structural component analysis

References

Abrams, D., Wetherell, M., Cochrane, S., Hogg, M. A., & Turner, J. C. (2001). Knowing what to think by knowing who you are: Self-categorization and the nature of norm formation, conformity and group polarization. In M. A. Hogg, & D. Abrams (Eds.), Intergroup relations: Essential readings (pp. 270-288). Psychology Press.
Alturki, U., & Aldraiweesh, A. (2021). Application of learning management system (LMS) during the COVID-19 pandemic: A sustainable acceptance model of the expansion technology approach. Sustainability, 13(19), 10991. https://doi.org/10.3390/su131910991
Ansong-Gyimah, K. (2020). Students’ perceptions and continuous intention to use e-learning systems: The case of Google Classroom. International Journal of Emerging Technologies in Learning, 15(11), 236-244. https://doi.org/10.3991/ijet.v15i11.12683
Bervell, B. (2018). Distance education tutors’ acceptance of learning management system for blended learning in Ghana [Unpublished doctoral thesis]. Universiti Sains Malaysia.
Bervell, B., & Arkorful, V. (2020). LMS-enabled blended learning utilization in distance tertiary education: Establishing the relationships among facilitating conditions, voluntariness of use and use behaviour. International Journal of Educational Technology in Higher Education, 17(1), 1-16. https://doi.org/10.1186/s41239-020-0183-9
Bervell, B., & Umar, I. N. (2017). Validation of the UTAUT model: Re-considering non-linear relationships of exogeneous variables in higher education technology acceptance research. Eurasia Journal of Mathematics, Science and Technology Education, 13(10), 6471-6490. https://doi.org/10.12973/ejmste/78076
Bervell, B., Kumar, J. A., Arkorful, V., Agyapong, E. M., & Osman, S. (2021). Remodelling the role of facilitating conditions for Google Classroom acceptance: A revision of UTAUT2. Australasian Journal of Educational Technology, 38(1),115-135. https://doi.org/10.14742/ajet.7178
Bervell, B., Nyagorme, P., & Arkorful, V. (2020). LMS-enabled blended learning use intentions among distance education tutors: Examining the mediation role of attitude based on technology-related stimulus-response theoretical framework. Contemporary Educational Technology, 12(2), ep273. https://doi.org/10.30935/cedtech/8317
Bonsu, N. O., Bervell, B., Armah, J. K., Aheto, S. P. K., & Arkorful, V. (2021). WhatsApp use in teaching and learning during COVID-19 pandemic period: Investigating the initial attitudes and acceptance of students. https://digitalcommons.unl.edu/libphilprac/6362/
Brown, S. A., Massey, A. P., Montoya-Weiss, M. M., & Burkman, J. R. (2002). Do I really have to? User acceptance of mandated technology. European Journal of Information Systems, 11(4), 283-295. https://doi.org/10.1057/palgrave.ejis.3000438
Celik, H. (2011). Influence of social norms, perceived playfulness and online shopping anxiety on customers’ adoption of online retail shopping: An empirical study in the Turkish context. International Journal of Retail & Distribution Management, 39(6), 390-413. https://doi.org/10.1108/09590551111137967
Chen, L. (2022). Designing online discussion for HyFlex learning. International Journal of Educational Methodology, 8(1), 191-198. https://doi.org/10.12973/ijem.8.1.191
Chiu, T. M., & Ku, B. P. (2015). Moderating effects of voluntariness on the actual use of electronic health records for allied health professionals. JMIR Medical Informatics, 3(1), e7.1-e7.10. https://doi.org/10.2196/medinform.2548
Cronbach, L. J. (1990). Essentials of psychological testing. Harper & Row.
Donaldson, R. L. (2011). Student acceptance of mobile learning [Unpublished PhD thesis]. Florida State University.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling. SAGE. https://doi.org/10.15358/9783800653614
Hamzat, S. A., & Mabawonku, I. (2018). Influence of performance expectancy and facilitating conditions on use of digital library by engineering lecturers in universities in south-west, Nigeria. https://digitalcommons.unl.edu/libphilprac/1670/
Hartwick, J., & Barki, H. (1994). Explaining the role of user participation in information systems use. Management Science 40(4), 440-465. https://doi.org/10.1287/mnsc.40.4.440
Henseler J. (2012). Why generalized structured component analysis is not universally preferable to structural equation modeling. Journal of the Academy of Marketing Science, 40, 402-413. https://doi.org/10.1007/s11747-011-0298-6
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Hurst, K. R. (2010). Technology acceptance in a mandatory technology-based learning environment [PhD thesis, The University of West Florida].
Hwang, H. (2008). VisualGSCA 1.0–A graphical user interface software program for generalized structured component analysis. In K. Shigemasu, A. Okada, T. Imaizumi, & T. Hoshino (Eds.), New trends in psychometrics (pp. 111-120). University Academic Press.
Hwang, H., DeSarbo S. W., & Takane Y. (2007). Fuzzy clusterwise generalized structured component analysis. Psychometrika, 72, 181. https://doi.org/10.1007/s11336-005-1314-x
Johnson, A. M., Jacovina, M. E., Russell, D. E., & Soto, C. M. (2016). Challenges and solutions when using technologies in the classroom. In S. A. Crossley, & D. S. McNamara (Eds.), Adaptive educational technologies for literacy instruction (pp. 13-29). Taylor & Francis. https://doi.org/10.4324/9781315647500-2
Jöreskog, K. G. (1970). A general method for estimating a linear structural equation system. In A. S. Goldberger, & O. D. Duncan(Eds.), Structural equation models in the social sciences (pp. 85-112). Seminar Press. https://doi.org/10.1002/j.2333-8504.1970.tb00783.x
Kaiser, H. (1974). An index of factor simplicity. Psychometrika, 39, 31-36. https://doi.org/10.1007/BF02291575
Kamaghe, J., Luhanga, E., & Kisangiri, M. (2020). The challenges of adopting m-learning assistive technologies for visually impaired learners in higher learning institution in Tanzania. International Journal of Emerging Technologies in Learning, 15(1), 140-151. https://doi.org/10.3991/ijet.v15i01.11453
Kim, J., & Park, H. S. (2011). The effect of uniform virtual appearance on conformity intention: Social identity model of deindividuation effects and optimal distinctiveness theory. Computers in Human Behavior, 27(3), 1223-1230. https://doi.org/10.1016/j.chb.2011.01.002
Kline, R. B. (2015). Principles and practice of structural equation modelling methodology in the social sciences. Guilford Publication.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308
Lascu, D.-N., & Zinkhan, G. (1999). Consumer conformity: Review and applications for marketing theory and practice. Journal of Marketing Theory and Practice, 7(3), 1-12. https://doi.org/10.1080/10696679.1999.11501836
Lwoga, E. T., & Komba, M. (2015). Antecedents of continued usage intentions of web-based learning management system in Tanzania. Education+Training, 57(7), 738-756. https://doi.org/10.1108/ET-02-2014-0014
Margahana, H., & Garaika, A. (2019. The influence of credibility and voluntariness toward technological use behavior: Entrepreneurial potential model approach. International Journal of Entrepreneurship, 23(2), 1-9.
Mtebe, J. S. (2020). Examining eLearning system self-efficacy amongst instructors at the University of Dodoma, Tanzania. Open Praxis, 12(3), 343-357. https://doi.org/10.5944/openpraxis.12.3.1103
Pynoo, B., Tondeur, J., van Braak, J., Duyck, W., Sijnave, B., & Duyck, P. (2011). Assessing teachers’ acceptance of educational technologies: Beware for the congruency between user acceptance and actual use. In T. Hirashima (Ed.), Proceedings of the 19^th International Conference on Computers in Education. Ghent University, Department of Educational Studies. https://doi.org/10.1016/j.compedu.2011.12.026
Radovan, M., & Kristl, N. (2017). Acceptance of technology and its impact on teachers’ activities in virtual classroom: Integrating UTAUT and CoI into a combined model. Turkish Online Journal of Educational Technology, 16(3), 11-22.
Ramlo, S. (2021). The coronavirus and higher education: Faculty viewpoints about universities moving online during a worldwide pandemic. Innovative HigherEducation, 46, 241-259. https://doi.org/10.1007/s10755-020-09532-8
Rawstorne, P., Jayasuriya, R., & Caputi, P. (2000). Issues in predicting and explaining usage behaviors with the technology acceptance model and the theory of planned behavior when usage is mandatory. Proceedings of ICIS 2000. Association for Information Systems.
Razkane, H., Sayeh, A. Y., & Yeou, M. (2022). University teachers’ attitudes towards distance learning during COVID-19 pandemic: Hurdles, challenges, and take-away lessons. European Journal of Interactive Multimedia and Education, 3(1), e02201. https://doi.org/10.30935/ejimed/11436
Richardson, J. W. (2011). Challenges of adopting the use of technology in less developed countries: The case of Cambodia. Comparative Education Review, 55(1), 008-029. https://doi.org/10.1086/656430
Ryoo, J. H., & Hwang, H. (2017). Model evaluation in generalized structured component analysis using confirmatory tetrad analysis. Frontiers in Psychology, 8, 916. https://doi.org/10.3389/fpsyg.2017.00916
Schlachter, S., McDowall, A., Cropley, M., & Inceoglu, I. (2018). Voluntary work-related technology use during non-work time: A narrative synthesis of empirical research and research agenda. International Journal of Management Reviews, 20(4), 825-846. https://doi.org/10.1111/ijmr.12165
Shin, H., & Dai, B. (2020). The efficacy of customer’s voluntary use of self-service technology (SST): A dual-study approach. Journal of Strategic Marketing. https://doi.org/10.1080/0965254X.2020.1841269
Srinivasan, R. (2015). Exploring the Impact of social norms and online shopping anxiety in the adoption of online apparel shopping by Indian consumers. Journal of Internet Commerce, 14(2), 177-199. https://doi.org/10.1080/15332861.2015.1008891
Taiwo, A. A., Downe, A. G., & Mahmood, A. K. (2012). User acceptance of eGovernment: Integrating risk and trust dimensions with UTAUT model [Conference session]. 2012 International Conference on Computer & Information Science, Kuala Lumpur, Malaysia. https://doi.org/10.1109/ICCISci.2012.6297222
Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163-184. https://doi.org/10.2190/EC.51.2.b
Van der Heuval, S. (2020). COVID-19 beats current technology acceptance theories. https://www.linkedin.com/pulse/covid-19-beats-current-technology-acceptance-theories-van-den-heuvel/
Vaportzis, E., Giatsi, C. M., & Gow, A. J. (2017). Older adults perceptions of technology and barriers to interacting with tablet computers: A focus group study. Frontiers in Psychology, 8, 1-11. https://doi.org/10.3389/fpsyg.2017.01687
Venkatesh, V., Brown, S.A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483-502. https://doi.org/10.2307/25148853
Venkatesh, V., Morris, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. MIS Quarterly, 33(2),419-432. https://doi.org/10.2307/20650298
Yeung, A. S., Taylor, P. G., Hui, C., Lam-Chiang, A. C., & Low. E.-L. (2012). Mandatory use of technology in teaching: Who cares and so what? British Journal of Educational Technology, 43(6), 859-870. https://doi.org/10.1111/j.1467-8535.2011.01253.x
Zagkos, C., Kyridis, A., Kamarianos, I., Dragouni, Κ. E., Katsanou, A., Kou-roumichaki, E., Papastergiou, N., & Stergianopoulos, E. (2022). Emergency remote teaching and learning in Greek universities during the COVID-19 pandemic: The attitudes of university students. European Journal of Interactive Multimedia and Education, 3(1),1-9. https://doi.org/10.30935/ejimed/11494
Zalat, M. M., Hamed, M. S., & Bolbol, S. A. (2021). The experiences, challenges, and acceptance of e-learning as a tool for teaching during the COVID-19 pandemic among university medical staff. Plos ONE, 16(3),1-12. https://doi.org/10.1371/journal.pone

Citation

Bervell, B., Umar, I. N., Masood, M., Kumar, J. A., Armah, J. K., & Somuah, B. A. (2022). Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education. Contemporary Educational Technology, 14(4), ep379. https://doi.org/10.30935/cedtech/12193

Bervell, B., Umar, I. N., Masood, M., Kumar, J. A., Armah, J. K., and Somuah, B. A. (2022). Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education. Contemporary Educational Technology, 14(4), ep379. https://doi.org/10.30935/cedtech/12193

Bervell B, Umar IN, Masood M, Kumar JA, Armah JK, Somuah BA. Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education. CONT ED TECHNOLOGY. 2022;14(4), ep379. https://doi.org/10.30935/cedtech/12193

Bervell, Brandford, Irfan Naufal Umar, Mona Masood, Jeya Amantha Kumar, Justice Kofi Armah, and Beatrice Asante Somuah. "Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education". Contemporary Educational Technology 2022 14 no. 4 (2022): ep379. https://doi.org/10.30935/cedtech/12193

Bervell, Brandford et al. "Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education". Contemporary Educational Technology, vol. 14, no. 4, 2022, ep379. https://doi.org/10.30935/cedtech/12193

Bervell B, Umar IN, Masood M, Kumar JA, Armah JK, Somuah BA. Promoting Voluntary Use Behavior of Learning Management Systems Among Tutors for Blended Learning in Distance Higher Education. CONT ED TECHNOLOGY. 2022;14(4):ep379. https://doi.org/10.30935/cedtech/12193