Factors Affecting Students’ Preferences for Online and Blended Learning: Motivational Vs. Cognitive

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Today’s educational institutions are expected to create learning opportunities independent of time and place, to offer easily accessible learning environments and interpersonal communication opportunities. Accordingly, higher education institutions develop strategies to meet these expectations through teaching strategies, such as e-learning, blended learning, mobile learning, etc., by using teaching technologies. These new technology-based teaching strategies are mainly shaped by decision-makers in education. This study seeks to analyse the individual factors that affect learners’ mode of teaching and learning delivery preferences. In this study, blended and online learning is considered as preferences of learners’ mode of teaching and learning delivery. The individual factors discussed in this research are cognitive learning strategies, e-learning readiness, and motivation. The data were obtained from the pre-service teachers at the end of the academic semester when they experienced online and blended learning. Data were analysed using optimal scaling analysis. The analysis method provides a two-dimensional centroid graph which shows the correlations between the variable categories. According to study findings, there is a correlation between the preferences of the learning environment, and the constructs of self-efficacy, e-learning motivation, and task value. It can be said that the motivational variables are more effective in the learning environment preference. The students with high task value, e-learning motivation, and self-efficacy preferred studying in blended learning environments. Cognitive strategies, self-directed learning, learner control, and test anxiety factors are independent of the learners’ learning delivery preferences.

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  • 1. Adam N. L. Alzahri F. B. Soh S. C. Bakar N. A. & Kamal N. A. M. (2017). Self-regulated learning and online learning: a systematic review. Proceedings of the International Visual Informatics Conference 143-154. Springer Cham.

  • 2. Artino Jr A. R. & Jones II K. D. (2012). Exploring the complex relations between achievement emotions and self-regulated learning behaviors in online learning. The Internet and Higher Education 15(3) 170-175.

  • 3. Atchley T. W. Wingenbach G. & Akers C. (2013). Comparison of course completion and student performance through online and traditional courses. The International Review of Research in Open and Distributed Learning 14(4).

  • 4. Barnard-Brak L. Lan W. Y. & Paton V. O. (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.

  • 5. Baturay M. H. & Yükseltürk E. (2015). The role of online education preferences on student’s achievement. Turkish Online Journal of Distance Education 16(3) 3-12.

  • 6. Bielawski L. & Metcalf D. (2003). Blended elearning: Integrating knowledge performance support and online learning. Amherst MA: HRD Press.

  • 7. Borotis S. & Poulymenakou A. (2004). E-learning readiness components: Key issues to consider before adopting e-learning interventions. E-Learn: World Conference on E-Learning in Corporate Government Healthcare and Higher Education 1622-1629. Association for the Advancement of Computing in Education (AACE).

  • 8. Broadbent J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. The Internet and Higher Education 33 24-32.

  • 9. Brown B. W. & Liedholm C. E. (2004). Student preferences in using online learning resources. Social Science Computer Review 22(4) 479-492.

  • 10. Butler T. J. & Pinto-Zipp G. (2005). Students’ learning styles and their preferences for online instructional methods. Journal of Educational Technology Systems 34(2) 199-221.

  • 11. Büyüköztürk Ş. Akgün Ö. E. Kahveci Ö. & Demirel F. (2004). Güdülenme ve öğrenme stratejileri ölçeğinin Türkçe formunun geçerlik ve güvenirlik çalışması. Kuram ve Uygulamada Eğitim Bilimleri 4(2) 207-239.

  • 12. Christensen C. M. Horn M. B. Caldera L. & Soares L. (2011 February 8). Disrupting college: How disruptive innovation can deliver quality and affordability to postsecondary education. The Center for American Progress [Blog post]. Retrieved from https://www.americanprogress.org/issues/economy/reports/2011/02/08/9034/disrupting-college/

  • 13. Cull S. Reed D. & Kirk K. (2010). Student motivation and engagement in online courses. In Authored as part of the 2010 workshop Teaching Geoscience Online-A Workshop for Digital Faculty.

  • 14. Dembo M. H. Junge L. G. & Lynch R. (2006). Becoming a self-regulated learner: Implications for web-based education. In H. F. O’Neil & R. S. Perez (Eds.) Web-based learning: Theory research and practice (pp. 185-202). Mahwah NJ US: Lawrence Erlbaum Associates Publishers.

  • 15. Guglielmino L. M. & Guglielmino P. J. (2003). Identifying learners who are ready for e-learning and supporting their success. In G. Piskurich (Ed.) Preparing learners for e-learning (pp. 18-33). San Francisco: Jossey-Bass.

  • 16. Hart C. (2012). Factors associated with student persistence in an online program of study: A review of the literature. Journal of Interactive Online Learning 11(1).

  • 17. Hung M. L. Chou C. Chen C. H. & Own Z. Y. (2010). Learner readiness for online learning: scale development and student perceptions. Computers & Education 55(3) 1080–1090. doi:10.1016/j.compedu.2010.05.004

  • 18. Joo Y. J. Lim K. Y. & Kim J. (2013). Locus of control self-efficacy and task value as predictors of learning outcome in an online university context. Computers & Education 62 149-158.

  • 19. Kaur K. & Zoraini Wati A. (2004). An assessment of e-learning readiness at Open University Malaysia. Proceedings of the International Conference on Computers in Education 2004 1017-1022.

  • 20. Kintu M. J. Zhu C. & Kagambe E. (2017). Blended learning effectiveness: the relationship between student characteristics design features and outcomes. International Journal of Educational Technology in Higher Education 14(1) 7.

  • 21. Kizilcec R. F. & Halawa S. (2015). Attrition and achievement gaps in online learning. Proceedings of the Second (2015) ACM Conference on Learning@ Scale 57-66. ACM.

  • 22. Lee J. Hong N. L. & Ling N. L. (2001). An analysis of students’ preparation for the virtual learning environment. The Internet and Higher Education 4(3-4) 231-242.

  • 23. Lim D. H. & Morris M. L. (2009). Learner and instructional factors influencing learning outcomes within a blended learning environment. Journal of Educational Technology & Society 12(4) 282.

  • 24. Lim D. H. Morris M. L. & Kupritz V. W. (2007). Online vs. blended learning: Differences in instructional outcomes and learner satisfaction. Journal of Asynchronous Learning Networks 11(2) 27-42.

  • 25. 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.

  • 26. López-Pérez M. V. Pérez-López M. C. & Rodríguez-Ariza L. (2011). Blended learning in higher education: Students’ perceptions and their relation to outcomes. Computers & Education 56(3) 818-826.

  • 27. Lumsden L. S. (1994). Student Motivation to Learn. Emergency Librarian 22(2) 31–32.

  • 28. Meulman J. J. & Heiser W. J. (2001). SPSS Categories 11.0. Retrieved from http://priede.bf.lu.lv/grozs/Datorlietas/SPSS/SPSSCategories11.0.pdf

  • 29. Muilenburg L. Y. & Berge Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance Education 26(1) 29-48.

  • 30. Najafi H. Rolheiser C. Harrison L. & Heikoop W. (2018). Connecting Learner Motivation to Learner Progress and Completion in Massive Open Online Courses. Canadian Journal of Learning and Technology 44(2) n2.

  • 31. NMC Horizon Report (2017). NMC Horizon Report: 2017 Higher Education Edition. Retrieved from http://cdn.nmc.org/media/2017-nmc-horizon-report-he-EN.pdf

  • 32. Padilla-MeléNdez A. Del Aguila-Obra A. R. & Garrido-Moreno A. (2013). Perceived playfulness gender differences and technology acceptance model in a blended learning scenario. Computers & Education 63 306-317.

  • 33. Park J. H. Lee E. & Bae S. H. (2010). Factors influencing learning achievement of nursing students in e-learning. Journal of Korean Academy of Nursing 40(2) 182-190.

  • 34. Pechenkina E. & Aeschliman C. (2017). What do students want? Making sense of student preferences in technology-enhanced learning. Contemporary Educational Technology 8(1) 26-39.

  • 35. Pintrich P. R. Smith D. Garcia T. & McKeachie W. (1991). A Manual for the Use of the Motivated Strategies for Learning Questionnaire (MSLQ). Ann Arbor MI: The University of Michigan.

  • 36. Raffo D. M. Gerbing D. W. & Mehta M. (2014). Understanding student preferences in online education. Proceedings of PICMET’14 Conference: Portland International Center for Management of Engineering and Technology; Infrastructure and Service Integration 1555-1564. IEEE.

  • 37. Ramli N. Muljono P. & Afendi F. M. (2018). The influencing factors of self directed learning readiness and academic achievement. Jurnal Kependidikan: Penelitian Inovasi Pembelajaran 2(1) 153-166.

  • 38. Richardson M. Abraham C. & Bond R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin 138(2) 353.

  • 39. Rosenberg J. & Ranellucci J. (2017 May 8). Student motivation in online science courses: A path to spending more time on course and higher achievement. Michigan Virtual Learning Research Institute [Blog post]. Retrieved from https://mvlri.org/blog/student-motivation-in-online-science-courses-a-path-to-spending-more-time-on-course-and-higher-achievement

  • 40. Rovai A. P. & Jordan H. (2004). Blended learning and sense of community: A comparative analysis with traditional and fully online graduate courses. The International Review of Research in Open and Distributed Learning 5(2).

  • 41. Selim H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education 49(2) 396-413.

  • 42. Sit J. W. Chung J. W. Chow M. C. & Wong T. K. (2005). Experiences of online learning: students’ perspective. Nurse Education Today 25(2) 140-147.

  • 43. Şahin M. Keskin S. Özgür A. & Yurdugül H. (2017). Determination of interaction profiles based on learner characteristics in e-learning environment. Educational Technology Theory and Practice 7(2) 172-192. doi: 10.17943/etku.297075

  • 44. Tsai C. C. (2005). Preferences toward Internet-based learning environments: High school students’ perspectives for science learning. Journal of Educational Technology & Society 8(2) 203-213.

  • 45. Valtonen T. Kukkonen J. Dillon P. & Väisänen P. (2009). Finnish high school students’ readiness to adopt online learning: Questioning the assumptions. Computers & Education 53(3) 742-748.

  • 46. Vanides J. (2018). Let’s Talk Online Learning. The New Media Consortium (NMC). Retrieved from https://www.nmc.org/blog/talking-sensibly-online-learning/

  • 47. Wang C. H. Shannon D. M. & Ross M. E. (2013). Students’ characteristics self-regulated learning technology self-efficacy and course outcomes in online learning. Distance Education 34(3) 302-323.

  • 48. Ward B. (2004). The best of both worlds: A hybrid statistics course. Journal of Statistics Education 12(3).

  • 49. Wojciechowski A. & Palmer L. B. (2005). Individual student characteristics: Can any be predictors of success in online classes. Online Journal of Distance Learning Administration 8(2) 13.

  • 50. Yang F. Y. & Tsai C. C. (2008). Investigating university student preferences and beliefs about learning in the web-based context. Computers & Education 50(4) 1284-1303.

  • 51. Yilmaz R. (2017). Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom. Computers in Human Behavior 70 251-260.

  • 52. Yurdugül H. & Demir Ö. (2017). An investigation of Pre-service Teachers’ Readiness for E-learning at Undergraduate Level Teacher Training Programs: The Case of Hacettepe University. H. U. Journal of Education 32 896-915.

  • 53. Zimmerman B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology 11(4) 307–313.

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