The role of quality factors in supporting self-regulated learning (SRL) skills in MOOC environment
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As a crucial factor that affects the learning performance in MOOC, self-regulated learning (SRL) has elicited considerable interest. Self-regulated learners can manage their learning activities efficiently, however, researchers indicate that MOOC learners do not adequately self-regulate their learning. Thus, providing support to facilitate self-regulated learning skill is important. This study examines the quality factors that affecting self-regulated learning in MOOC environment. Using a structured questionnaire derived from the literature, data was collected from 1000 undergraduate students from 5 public universities in Malaysia. The questionnaire consisted of 2 sections. The first section collected the demographic data, the second section educed data about self-regulated learning, information quality, service quality and system quality. Through Partial Least Squares Structural Equation Modeling (PLS-SEM) technique, the relationships between the quality factors and self-regulated learning were obtained. Statistical findings revealed that service quality factor influence self-regulated learning positively in MOOC. The findings provide by the study may give an empirically justified foundation for those who concerned to develop strategies for encouraging the adoption of MOOC.
KeywordsMassive open online courses MOOC Self-regulated learning SRL Quality factors
The appreciation goes to Dr. Farrah Dina Yusop for giving a moral support in the production of this paper.
Compliance with ethical standards
The author declares that there are no competing interests.
- Alraimi, K. M., Zo, H., & Ciganek, A. P. (2015). Understanding the MOOCs continuance: The role of openness and reputation. Computers & Education, 80, 28–38.Google Scholar
- Alsabawy, A. Y., Cater-Steel, A., and Soar, J. (2011). Measuring e-learning system success (research in progress). In Proceedings of the 15th Pacific Asia Conference on Information Systems (PACIS 2011, July) (pp. 1-15). Queensland University of Technology.Google Scholar
- Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2012). A model to measure e-learning systems success. In Measuring Organizational Information Systems Success: New Technologies and Practices (pp. 293–317). Hershey: Business Science Reference.Google Scholar
- Artino, A. R., & Stephens, J. M. (2009). Academic motivation and self-regulation: A comparative analysis of undergraduate and graduate students learning online. The Internet and Higher Education, 12(3), 146–151.Google Scholar
- Albelbisi, N., Yusop, F. D., & Salleh, U. K. M. (2018). Mapping the factors influencing success of massive open online courses (MOOC) in higher education. Eurasia Journal of Mathematics, Science and Technology Education, 14(7), 2995–3012.Google Scholar
- Barnard, L., Paton, V., & Lan, W. (2008). Online self-regulatory learning behaviors as a mediator in the relationship between online course perceptions with achievement. The International Review of Research in Open and Distributed Learning, 9(2), 1–11.Google Scholar
- Barnard-Brak, L., Paton, V. O., & Lan, W. Y. (2010). Profiles in self-regulated learning in the online learning environment. The International Review of Research in Open and Distributed Learning, 11(1), 61–80.Google Scholar
- Chen, C. M. (2009). Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance. Expert Systems with Applications, 36(5), 8816–8829.Google Scholar
- Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In A. George (Ed.), Modern methods for business research, 295(2), 295–336. Mahwah: Erlbaum.Google Scholar
- Chin, W. W., Marcolin, B., & Newsted, P. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217.Google Scholar
- Cho, M. H., & Kim, B. J. (2013). Students' self-regulation for interaction with others in online learning environments. The Internet and Higher Education, 17, 69–75.Google Scholar
- Daniel, J., & Uvalic-Trumbic, S. (2013). Turbulent times in tertiary education: Lessons for Bangladesh. Paper presented at the International Conference on Tertiary Education: Realities and Challenges, Daffodil University, Bangladesh.Google Scholar
- de Waard, I. (2011). Explore a new learning frontier: MOOCs. Learning Solutions Magazine, 25. Retrieved from https://www.learningsolutionsmag.com/articles/721/explore-a-new-learning-frontiermoocs.
- de Waard, I., Gallagher, M. S., Zelezny-Green, R., Czerniewicz, L., Downes, S., Kukulska-Hulme, A., & Willems, J. (2014). Challenges for conceptualising EU MOOC for vulnerable learner groups. Proceedings of the European MOOC Stakeholder Summit 2014 (pp. 33–42). Retrieved July 11, 2017, from http://oro.open.ac.uk/40381/2/deWaardEtAl.pdf.
- DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.Google Scholar
- Ehlers, U. D., Ossiannilsson, E., & Creelman, A. (2013). Week 1: MOOCs and Quality – Where are we – where do we go from here …? Retrieved from http://mooc.efquel.org/first-post-of-the-series/.
- Freeze, R. D., Alshare, K. A., Lane, P. L., & Wen, H. J. (2010). IS success model in ELearning context based on students’ perceptions. Journal of Information Systems Education, 21(2), 173–184.Google Scholar
- Gamage, D., Fernando, S., & Perera, I. (2015). Quality of MOOCs: A review of literature on effectiveness and quality aspects. In Ubi-Media Computing (UMEDIA), 2015 8th International Conference on (pp. 224–229). IEEE. Retrieved on 25 Oct 2016 from http://bit.ly/2dwJ3ZE.
- Glance, D. G., Forsey, M., & Riley, M. (2013). The pedagogical foundations of massive open online courses. First Monday, 18(5). https://doi.org/10.5210/fm.v18i5.4350.
- Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214.Google Scholar
- Grimmelmann, J. (2014). Merchants of MOOCs, Seton Hall Law Review, 44(4). Retrieved on 1 Nov 2016 from http://bit.ly/2dZuRKL.
- Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Jersey: Prentice Hall.Google Scholar
- Hair, J. F., Black, W. C., Babin, B., Anderson, R. E., & Ronald, L. T. (2006). Multivariate data analysis (5th ed.). Englewood Cliffs: Prentice Hall.Google Scholar
- Hair, J. F., Black, W. C., Babin, B., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Jersey: Prentice Hall.Google Scholar
- Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.Google Scholar
- Harrell, I. L. (2008). Increasing the success of online students. Inquiry, 13(1), 36–44.Google Scholar
- Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert Systems with Applications, 39(12), 10959–10966.Google Scholar
- Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in international marketing, 20, 277–319.Google Scholar
- Hood, N., & Littlejohn, A. (2016). Quality in MOOCs: Surveying the Terrain. Retrieved on October 21, 2017, from http://oasis.col.org/bitstream/handle/11599/2352/2015_QualityinMOOCs-Surveying-the-Terrain.pdf?sequence=1&isAllowed=y <https://urldefense.proofpoint.com/v2/url?u=http-3A__oasis.col.org_bitstream_handle_11599_2352_2015-5FQualityinMOOCs-2DSurveying-2Dthe-2DTerrain.pdf-3Fsequence-3D1-26isAllowed-3Dy&d=DwMFaQ&c=vh6FgFnduejNhPPD0fl_yRaSfZy8CWbWnIf4XJhSqx8&r=8IEA8RSOvQ9oXtWAG1eT2mTMD_NJ-ANv3H9feUw_xMw&m=NEykeoku9Df9P6A_Hxc79bWQEVO9SxDPi7SqM72APoE&s=dMPWG8NHauBmL_a_EbffxvN-p4CAy6cF3HwsMgMCx6I&e=>.
- Hood, N., Littlejohn, A., & Milligan, C. (2015). Context counts: How learners' contexts influence learning in a MOOC. Computers & Education, 91, 83–91.Google Scholar
- Hsu, Y. C., Ching, Y. H., Mathews, J. P., & Carr-Chellman, A. (2009). Undergraduate students'self-regulated learning experience in web-based learning environments. The Quarterly Review of Distance Education, 10(2), 109.Google Scholar
- Hu, H., & Gramling, J. (2009). Learning strategies for success in a web-based course: A descriptive exploration. The Quarterly Review of Distance Education, 10(2), 123.Google Scholar
- Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204.Google Scholar
- Jairam, D., & Kiewra, K. A. (2010). Helping students soar to success on computers: An investigation of the SOAR study method for computer-based learning. Journal of Educational Psychology, 102(3), 601–614.Google Scholar
- Jansen, D., Rosewell, J., & Kear, K. (2016). Quality Frameworks for MOOCs. In M. Jemni, Kinshuk & M.K. Khribi (Eds.), Open Education: from OERs to MOOCs. Lecture Notes in Educational Technology (LNET). (pp. 261–281) Aug 18, 2016. Berlin: Springer. Retrieved Jan 22, 2018, from https://www.springer.com/gp/book/9783662529232.
- Kizilcec, R. F., & Halawa, S. (2015). Attrition and achievement gaps in online learning. In Proceedings of the Second (2015) ACM Conference on Learning@ Scale (pp. 57-66). ACM.Google Scholar
- Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2016). Recommending self-regulated learning strategies does not improve performance in a MOOC. In Proceedings of the Third (2016) ACM Conference on Learning@ Scale (pp. 101-104). ACM.Google Scholar
- Kop, R. (2011). The challenges to connectivist learning on open online networks: Learning experiences during a massive open online course. The International Review of Research in Open and Distributed Learning, 12(3), 19–38.Google Scholar
- Lee, J. K., & Lee, W. K. (2008). The relationship of e-Learner's self-regulatory efficacy and perception of e-learning environmental quality. Computers in Human Behaviour, 24(1), 32–47.Google Scholar
- Li, C. S., & Irby, B. (2008). An overview of online education: Attractiveness, benefits, challenges, concerns and recommendations. College Student Journal, 42(2), 499–458.Google Scholar
- Liaw, S. S., & Huang, H. M. (2013). Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments. Computers & Education, 60(1), 14–24.Google Scholar
- Littlejohn, A., & Milligan, C. (2015). Designing MOOCs for professional learners: Tools and patterns to encourage self-regulated learning. eLearning Papers, 42, 38–45.Google Scholar
- Littlejohn, A., Hood, N., Milligan, C., & Mustain, P. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. The Internet and Higher Education, 29, 40–48.Google Scholar
- Liyanagunawardena, T. R., Adams, A. A., & Williams, S. A. (2013). MOOCs: A systematic study of the published literature 2008-2012. The International Review of Research in Open and Distance Learning, 14(3), 202–227. Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1455/2531.
- Malik, M. W. (2010). Factors effecting learner’s satisfaction towards E-learning: A conceptual framework. OIDA. International Journal of Sustainable Development, 2(3), 77–82. Retrieved Aug 1, 2017, from http://www.ssrn.com/link/OIDA-Intl-Journal-Sustainable-Dev.html.
- Matuga, J. M. (2009). Self-regulation, goal orientation, and academic achievement of secondary students in online university courses. Journal of Educational Technology & Society, 12(3), 4.Google Scholar
- McAuley, A., Stewart, B., Siemens, G., & Cormier, D. (2010). In the open: The MOOC model for digital practice. Charlottetown, Canada: University of Prince Edward Island. Retrieved on May 18, 2017, from https://oerknowledgecloud.org/sites/oerknowledgecloud.org/files/MOOC_Final.pdf <https://www.oerknowledgecloud.org/sites/oerknowledgecloud.org/files/MOOC_Final.pdf <https://urldefense.proofpoint.com/v2/url?u=https-3A__oerknowledgecloud.org_sites_oerknowledgecloud.org_files_MOOC-5FFinal.pdf&d=DwMFaQ&c=vh6FgFnduejNhPPD0fl_yRaSfZy8CWbWnIf4XJhSqx8&r=8IEA8RSOvQ9oXtWAG1eT2mTMD_NJ-ANv3H9feUw_xMw&m=NEykeoku9Df9P6A_Hxc79bWQEVO9SxDPi7SqM72APoE&s=4l0RP5X_miWmBTPRMCfrJ1um_aiFdcYz-p4toU57FCQ&e=>.
- Milligan, C., Littlejohn, A., & Margaryan, A. (2013). Patterns of engagement in connectivist MOOCs. MERLOT Journal of Online Learning and Teaching, 9(2), 149–159.Google Scholar
- Musa, A. M., & Othman, M. O. (2012). Critical success factors in E-learning: An examination of technology and students factors. International Journal of Advances in Engineering and Technology (IJAET), 3(2), 140–148.Google Scholar
- Nawrot, I., & Doucet, A. (2014). Building engagement for MOOC students: Introducing support for time management on online learning platforms. Paper presented at the 23rd International World Wide Web Conference, Seoul, South Korea. https://doi.org/10.1145/2567948.2580054.
- Nordin, N., Norman, H., & Embi, M. A. (2015). Technology acceptance of massive open online courses in Malaysia. Malaysian Journal of Distance Education, 17(2), 1–16.Google Scholar
- Onah, D. F. O., & Sinclair, J. E. (2017). Assessing self-regulation of learning dimensions in a stand-alone MOOC platform. International Journal of Engineering Pedagogy (iJEP), 7(2), 4–21.Google Scholar
- Ozkan, S., Koseler, R., & Baykal, N. (2009). Evaluating learning management systems: Adoption of hexagonal e-learning assessment model in higher education. Transforming Government: People, Process and Policy, 3(2), 111–130.Google Scholar
- Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236–263.Google Scholar
- Rai, L., & Chunrao, D. (2016). Influencing factors of success and failure in MOOC and general analysis of learner behavior. International Journal of Information and Education Technology, 6(4), 262–268.Google Scholar
- Ramayah, T., & Lee, J. W. C. (2012). System characteristics, satisfaction and elearning usage: A structural equation model (SEM). The Turkish Online Journal of Education Technology, 11(2), 196–206.Google Scholar
- Ringle, C. M., Wende, S., & Becker, J-M. (2015). SmartPLS 3. Hamburg, Germany: SmartPLS. Retrieved Aug 17, 2017, from http://www.smartpls.com.
- Samarasinghe, S. M. (2012). E-learning systems success in an organisational context: A thesis presented in partial fulfilment of the requirements for the degree of doctor of philosophy in management information Systems at Massey University, Palmerston North, New Zealand (Doctoral dissertation, Massey University). Retrieved from http://hdl.handle.net/10179/4726
- Tella, A. (2011). Reliability and factor analysis of a blackboard course management system success: A scale development and validation in an educational context. Journal of Information Technology Education: Research, 10, 55–80.Google Scholar
- Terras, M. M., & Ramsay, J. (2015). Massive open online courses (MOOCs): Insights and challenges from a psychological perspective. British Journal of Educational Technology, 46(3), 472–487.Google Scholar
- Thirouard, M., Bernaert, O., Dhorne, L., Bianchi, S., Pidol, L., & Petit, Y. (2015). Learning by doing: Integrating a serious game in a MOOC to promote new skills. Proceedings Papers, 92.Google Scholar
- Thomas, C. R., & Gadbois, S. A. (2007). Academic self-handicapping: The role of self-concept clarity and students' learning strategies. British Journal of Educational Psychology, 77(1), 101–119.Google Scholar
- Wang, H. C., & Chiu, Y. F. (2011). Assessing e-learning 2.0 system success. Computers & Education, 57(2), 1790–1800.Google Scholar
- Yakubu, M. N., & Dasuki, S. (2018). Assessing eLearning systems success in Nigeria: An application of the DeLone and McLean information systems success model. Journal of Information Technology Education: Research, 17, 183–203.Google Scholar
- Yousef, A. M. F., Chatti, M. A., Schroeder, U., & Wosnitza, M. (2014). What drives a successful MOOC? An empirical examination of criteria to assure design quality of MOOCs. In Advanced Learning Technologies (ICALT), 2014 IEEE 14th International Conference on (pp. 44-48). IEEE.Google Scholar
- Zhao, H. (2016). Factors influencing self-regulation in e-learning 2.0: Confirmatory factor model. Canadian Journal of Learning and Technology, 42, 2–22.Google Scholar
- Zimmerman, B. J. (1989). Models of self-regulated learning and academic achievement. In Self-regulated learning and academic achievement (pp. 1–25). New York: Springer.Google Scholar
- Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In Handbook of metacognition in education (pp. 311–328). New York: Routledge.Google Scholar