A Conceptual Persuasive Development Framework to Change Students’ Behaviour in Massive Open Online Courses: A Review
Abstract
Some experts attribute the relatively low completion rates of Massive Open Online Courses (MOOCs) partly to user dissatisfaction with the system. Live instructors are absent from MOOCs due to their delivery through virtual learning platforms. A distinctive feature distinguishing MOOCs from other e-learning systems is the significantly higher ratio between users and instructors. Consequently, the main challenges include limited interaction between students and study materials and the heightened need for instructor guidance. Consequently, enhancing the design of the existing MOOCs system is imperative to create a more engaging learning experience. Previous studies have attempted to incorporate persuasive design elements into e-learning systems. However, these studies must integrate persuasive design with motivational factors and effective learning strategies to encourage student behavior change and increase student engagement. The present study utilizes prior literature to establish a conceptual framework for persuasive e-learning development, known as PEDAL, which integrates motivational factors, learning strategies, and persuasive design principles. The initial section of the paper introduces issues related to student motivation, learning strategies, the MOOCs platform, and the potential impact of persuasive technology on enhancing the effectiveness of MOOCs. The subsequent section elucidates the methodology employed for the literature search. The third section explains the mechanisms of the PEDAL framework and discusses relevant previous literature that contributed to its development. Finally, the last section outlines the framework's limitations and potential future improvement. The paper also outlines how the proposed conceptual framework can be applied to design an effective e-learning system.
https://doi.org/10.26803/ijlter.22.9.1
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Ariely, D., & Wertenbroch, K. (2002). Procrastination, Deadlines, and Performance: Self-Control by Precommitment. Psychological Science, 13(3).
Attewell, Jill., Savill-Smith, Carol., & Great Britain. Learning and Skills Development Agency. (2005). Mobile learning anytime everywhere: a book of papers from MLEARN 2004. Learning and Skills Development Agency.
Batsila, M., Tsihouridis, C., Vavougios, D., & Ioannidis, G. S. (2015). Factors that influence the application of Web 2.0 based techniques for instructional purposes - A case study. International Journal of Emerging Technologies in Learning, 10(4), 15–21. https://doi.org/10.3991/ijet.v10i4.4529
Behringer, R., & Øhrstrøm, P. (2013). Persuasive Design in Teaching and Learning. International Journal of Conceptual Structures and Smart Applications, 1(2), 1–5. https://doi.org/10.4018/ijcssa.2013070101
Belo, R., Ferreira, P., & Telang, R. (2014). Broadband in school: Impact on student performance. Management Science, 60(2), 265–282. https://doi.org/10.1287/mnsc.2013.1770
Chen, O., Woolcott, G., & Sweller, J. (2017). Using cognitive load theory to structure computer-based learning including MOOCs. In Journal of Computer Assisted Learning (Vol. 33, Issue 4, pp. 293–305). Blackwell Publishing Ltd. https://doi.org/10.1111/jcal.12188
Cilliers, L., Twinomurinzi, H., & Murire, O. (2023). Motivational Factors that Influence the Course Completion Rate of Massive Open Online Courses in South Africa. International Journal of Learning, Teaching and Educational Research, 22(6), 195–211. https://doi.org/10.26803/ijlter.22.6.12
Dohnke, B., Weiss-Gerlach, E., & Spies, C. D. (2011). Social influences on the motivation to quit smoking: Main and moderating effects of social norms. Addictive Behaviors, 36(4), 286–293. https://doi.org/10.1016/j.addbeh.2010.11.001
Filippou, J., Cheong, C., & Cheong, F. (2015). Combining the Fogg Behavioural Model and Hook Model To Design Features in a Persuasive App To Improve Study Habits. Australasian Conference on Information Systems.
Filippou, J., Cheong, C., & Cheong, F. (2016). Modelling the Impact of Study Behaviours on Academic Performance to Inform the Design of a Persuasive System. Information and Management, 53(7), 892–903. https://doi.org/10.1016/j.im.2016.05.002
Fischer, H. (2013). E-Learning im Lehralltag: Analyse der Adoption von E-Learning-Innovationen in der Hochschullehre. https://doi.org/10.1007/978-3-658-02182-5
Fogg, B. J. (2009a). A Behavior Model for Persuasive Design.
Fogg, B. J. (2009b). Creating Persuasive Technologies: An Eight-Step Design Process. 91, 1–6. https://doi.org/10.1145/1541948.1542005
Fogg, B. J. (2012). Persuasive Technology, Using Computers to Change What We Think and Do. Encyclopedia of Applied Ethics, 431–437. https://doi.org/10.5195/CINEJ.2011.14
Fritzsche, B. A., Young, B. R., & Hickson, K. C. (2003). Individual differences in academic procrastination tendency and writing success. Personality and Individual Differences, 35(7), 1549–1557. www.elsevier.com/locate/paid
Gbollie, C., & Keamu, H. P. (2017). Student Academic Performance: The Role of Motivation, Strategies, and Perceived Factors Hindering Liberian Junior and Senior High School Students Learning. Education Research International, 2017, 1–11. https://doi.org/10.1155/2017/1789084
Gram-hansen, & Sandra, B. (2012). PLOT Persuasive Learning Design Framework. Persuasive Learning Objects and Technologies for Lifelong Learning in Europe Publication.
Greene, J. A., Moos, D. C., & Azevedo, R. (2011). Self-regulation of learning with computer-based learning environments. New Directions for Teaching and Learning, 126, 107–115. https://doi.org/10.1002/tl.449
Griese, B. (2016). Learning Strategies in Engineering Mathematics- Conceptualisation, Development, and Evaluation of MP 2-Mathe/Plus Dissertation.
Haba, H. F., & Dastane, O. (2019). Massive open online courses (MOOCs) - Understanding online learners’ preferences and experiences. International Journal of Learning, Teaching and Educational Research, 18(8), 227–242. https://doi.org/10.26803/ijlter.18.8.14
Harjumaa, M., & Muuraiskangas, S. (2014). Building Persuasiveness into Information Systems. Electronic Journal of Information Systems Evaluation, 17(1), 23–35. www.ejise.com
Haron, H., Mohd Yusof, A. R., Samad, H., Ismail, N., Juanita, A., & Yusof, H. (2019). the Platform of Mooc (Massive Open Online Course) on Open Learning: Issues and Challenges. International Journal of Modern Education, 1(3), 01–09. https://doi.org/10.35631/ijmoe.13001
Hood, N., Littlejohn, A., & Milligan, C. (2015). Context counts: How learners’ contexts influence learning in a MOOC. Computers and Education, 91, 83–91. https://doi.org/10.1016/j.compedu.2015.10.019
Huang, N., Zhang, J., Burtch, G., Li, X., & Chen, P. (2018). Combating Procrastination on MOOCs via Optimal Calls-to-Action: Evidence from a Field Experiment. Academy of Management Proceedings, 2018(1), 14171. https://doi.org/10.5465/ambpp.2018.14171abstract
Kaldo, I., & Õun, K. (2020). The Factor Structure of List Questionnaire for Learning Strategies of Estonian Students in Mathematics. In International Journal of Education and Social Science Research (Vol. 3, Issue 02). http://ijessr.com
Kelders, S. M., Kok, R. N., Ossebaard, H. C., & Van Gemert-Pijnen, J. E. W. C. (2012). Persuasive system design does matter: A systematic review of adherence to web-based interventions. In Journal of Medical Internet Research (Vol. 14, Issue 6). JMIR Publications Inc. https://doi.org/10.2196/jmir.2104
Khalil, M., & Ebner, M. (2017). Clustering patterns of engagement in Massive Open Online Courses (MOOCs): the use of learning analytics to reveal student categories. Journal of Computing in Higher Education, 29(1), 114–132. https://doi.org/10.1007/s12528-016-9126-9
Khan, A., Egbue, O., Palkie, B., & Madden, J. (2017). Active learning: Engaging students to maximize learning in an online course. Electronic Journal of E-Learning, 15(2), 107–115.
Kim, K. R., & Seo, E. H. (2015). The relationship between procrastination and academic performance: A meta-analysis. Personality and Individual Differences, 82, 26–33. https://doi.org/10.1016/j.paid.2015.02.038
Kizilcec, R. F., Piech, C., & Schneider, E. (2013). Deconstructing disengagement: Analyzing learner subpopulations in massive open online courses. ACM International Conference Proceeding Series. https://doi.org/10.1145/2460296.2460330
Kloft, M., Stiehler, F., Zheng, Z., & Pinkwart, N. (2014). Predicting MOOC Dropout over Weeks Using Machine Learning Methods. The 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 60–65.
Korableva, O., Durand, T., Kalimullina, O., & Stepanova, I. (2019). Studying user satisfaction with the MOOC platform interfaces using the example of coursera and open education platforms. ACM International Conference Proceeding Series, 26–30. https://doi.org/10.1145/3322134.3322139
Lee, D., Lee Watson, S., & Watson, W. R. (2020). The Influence of Successful MOOC Learners’ Self-Regulated Learning Strategies, Self-Efficacy, and Task Value on Their Perceived Effectiveness of a Massive Open Online Course The Influence of Successful MOOC Learners’ Self-Regulated Learning Strategies, Self-Efficacy, and Task Value on Their Perceived Effectiveness. In International Review of Research in Open and Distributed Learning (Vol. 21).
Loh, Y. X., & Hamid, N. A. B. A. (2021). The evaluation of online persuasion criteria on e-commerce website using persuasive system design (PSD) model. International Journal of Business and Society, 22(3), 1143–1157. https://doi.org/10.33736/ijbs.4289.2021
Magulod, G. C. (2019). Learning styles, study habits and academic performance of Filipino university students in applied science courses: Implications for instruction. Journal of Technology and Science Education, 9(2), 184–198. https://doi.org/10.3926/jotse.504
Marotta, V., & Acquisti, A. (2017). Online Distractions, Website Blockers, and Economic Productivity: A Randomized Field Experiment. The Workshop on the Economics of Information Security (WEIS). https://www.rescuetime.com/,
Mhd Salim, M. H., Ali, N. M., & Ijab, M. T. (2019a). Understanding students’ motivation and learning strategies to redesign massive open online courses based on persuasive system development. International Journal of Advanced Computer Science and Applications, 10(12), 234–241.
Mhd Salim, M. H., Ali, N. M. N. M., & Ijab, M. T. M. T. (2019b). Understanding students’ motivation and learning strategies to redesign massive open online courses based on persuasive system development. International Journal of Advanced Computer Science and Applications, 10(12), 234–241.
Mhd Salim, M. H., & Mohamad Ali, N. (2019). Mapping Learning Strategies and Motivation with Persuasive Principles to Inform the Design Application. International Conference on Education & Language for Students and Adult Learners, September, 227–234.
Modise, M. E. P. (2022). The Potentiality of MOOCs as a Tool for Widening Access to Higher Education in the African Context: A Systematic Review. In International Journal of Learning, Teaching and Educational Research (Vol. 21, Issue 5, pp. 84–103). Society for Research and Knowledge Management. https://doi.org/10.26803/ijlter.21.5.5
Moore, M. J. (2005). The Transtheoretical Model of the Stages of Change and the Phases of Transformative Learning: Comparing Two Theories of Transformational Change. Journal of Transformative Education, 3(4), 394–415. https://doi.org/10.1177/1541344605279386
Newman, R., Chang, V., Walters, R. J., & Wills, G. B. (2016). Web 2.0 - The past and the future. International Journal of Information Management, 36(4), 591–598. https://doi.org/10.1016/j.ijinfomgt.2016.03.010
Nikolayeva, I., Yessad, A., Laforge, B., & Luengo, V. (2020). Does an e-mail reminder intervention with learning analytics reduce procrastination in a blended university course? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12315 LNCS, 60–73. https://doi.org/10.1007/978-3-030-57717-9_5
Nordin, N., Norman, H., & Embi, M. A. (2016). Technology Acceptance of Massive Open Online Courses in Malaysia. Malaysian Journal of Distance Education, 17(2), 1–16. https://doi.org/10.21315/mjde2015.17.2.1
Oinas-Kukkonen, H. (2013). A foundation for the study of behavior change support systems. Personal and Ubiquitous Computing, 17(6), 1223–1235. https://doi.org/10.1007/s00779-012-0591-5
Oinas-Kukkonen, H., & Harjumaa, M. (2008). A Systematic Framework for Designing and Evaluating Persuasive Systems. Persuasive Technology, Third International Conference, PERSUASIVE 2008, Oulu, Finland, June 4-6, 2008. Proceedings, 164–176. https://www.researchgate.net/publication/220962680_A_Systematic_Framework_for_Designing_and_Evaluating_Persuasive_Systems
Oinas-kukkonen, H., & Harjumaa, M. (2009). Communications of the Association for Information Systems Persuasive Systems Design : Key Issues , Process Model , and System Features Persuasive Systems Design : Key Issues , Process Model , and System Features. Communications of the Association for Information Systems, 24(28), 485–500.
Onah, D. F. O., Sinclair, J., & Boyatt, R. (2014). Dropout Rates of Massive Open Online Courses: Behavioural Patterns. 6th International Conference on Education and New Learning Technologies (EDULEARN14), 5825–5834.
Paul R., P., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A Manual for the Use of the Motivated Strategies for Learning Questionnaire (MSLQ) Motivated Strategies for Learning Questionnaire Manual. https://doi.org/doi: 10.13140/RG.2.1.2547.6968.
Prince, M. (2004). Does active learning work? A review of the research. In Journal of Engineering Education (Vol. 93, Issue 3, pp. 223–231). Wiley-Blackwell Publishing Ltd. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x
Rabin, L. A., Fogel, J., & Nutter-Upham, K. E. (2011). Academic procrastination in college students: The role of self-reported executive function. Journal of Clinical and Experimental Neuropsychology, 33(3), 344–357. https://doi.org/10.1080/13803395.2010.518597
Sethi, R. (2017). Studying unintended consequences of using MOOC interface: An affordance perspective to address the dropout problem in MOOCs. ACM International Conference Proceeding Series, Part F128003, 621–624. https://doi.org/10.1145/3047273.3047364
Sherimon, V., Sherimon, P. C., Francis, L., Devassy, D., & George, T. K. (2021). Factors associated with Student enrollment, completion, and dropout of massive open online courses in the Sultanate of Oman. International Journal of Learning, Teaching and Educational Research, 20(11), 154–169. https://doi.org/10.26803/ijlter.20.11.9
Shukor, N. A., & Abdullah, Z. (2019). Using learning analytics to improve MOOC instructional design. International Journal of Emerging Technologies in Learning, 14(24), 6–17. https://doi.org/10.3991/ijet.v14i24.12185
Sinha, T., Li, N., Jermann, P., & Dillenbourg, P. (2014). Capturing “attrition intensifying” structural traits from didactic interaction sequences of MOOC learners. Proceedings of the EMNLP 2014 Workshop on Analysis of Large-Scale Social Interaction in MOOCs, 42–49. http://arxiv.org/abs/1409.5887
Soemantri, D., McColl, G., & Dodds, A. (2018). Measuring medical students’ reflection on their learning: Modification and validation of the motivated strategies for learning questionnaire (MSLQ). BMC Medical Education, 18(1), 1–10. https://doi.org/10.1186/s12909-018-1384-y
Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94. https://doi.org/10.1037/0033-2909.133.1.65
Stracke, C. M. (2017). The quality of MOOCs: How to improve the design of Open Education and online courses for learners? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10295 LNCS, 285–293. https://doi.org/10.1007/978-3-319-58509-3_23
Weinstein, C. E., Palmer, D. R., & Acee, T. W. (2016). Learning and Study Strategies Inventory LASSI Third Edition User’s Manual (3rd ed.). H&H Publishing Company, Inc. www.hhpublishing.com
Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G. J., & Paas, F. (2019). Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review. International Journal of Human-Computer Interaction, 35(4–5), 356–373. https://doi.org/10.1080/10447318.2018.1543084
You, H. W. (2019). Students’ Perception about Learning using MOOC. International Journal of Emerging Technologies in Learning (IJET), 14(18), 203. https://doi.org/10.3991/ijet.v14i18.10802
Zeng, S., Gonzalez, J., & Lobato, C. (2015). The effect of organizational learning and Web 2.0 on innovation. Management Decision, 53(9), 2060–2072. https://doi.org/10.1108/MD-06-2014-0388
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