1. bookVolume 22 (2019): Issue 2 (December 2019)
Journal Details
License
Format
Journal
eISSN
1027-5207
First Published
11 Dec 2014
Publication timeframe
2 times per year
Languages
English
access type Open Access

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

Published Online: 24 Jan 2020
Volume & Issue: Volume 22 (2019) - Issue 2 (December 2019)
Page range: 72 - 86
Journal Details
License
Format
Journal
eISSN
1027-5207
First Published
11 Dec 2014
Publication timeframe
2 times per year
Languages
English
Abstract

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.

Keywords

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.10.1007/978-3-319-70010-6_14 Search in Google Scholar

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), 170-175.10.1016/j.iheduc.2012.01.006 Search in Google Scholar

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).10.19173/irrodl.v14i4.1461 Search in Google Scholar

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), 61-80.10.19173/irrodl.v11i1.769 Search in Google Scholar

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), 3-12.10.17718/tojde.47810 Search in Google Scholar

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

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). Search in Google Scholar

8. Broadbent, J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. The Internet and Higher Education, 33, 24-32.10.1016/j.iheduc.2017.01.004 Search in Google Scholar

9. Brown, B. W., & Liedholm, C. E. (2004). Student preferences in using online learning resources. Social Science Computer Review, 22(4), 479-492.10.1177/0894439304268529 Search in Google Scholar

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), 199-221.10.2190/8UD2-BHFU-4PXV-7ALW Search in Google Scholar

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. Search in Google Scholar

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/ Search in Google Scholar

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. Search in Google Scholar

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. Search in Google Scholar

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. Search in Google Scholar

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). Search in Google Scholar

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.2010.05.00410.1016/j.compedu.2010.05.004 Search in Google Scholar

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, 149-158.10.1016/j.compedu.2012.10.027 Search in Google Scholar

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. Search in Google Scholar

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), 7.10.1186/s41239-017-0043-4 Search in Google Scholar

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.10.1145/2724660.2724680 Search in Google Scholar

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), 231-242.10.1016/S1096-7516(01)00063-X Search in Google Scholar

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. Search in Google Scholar

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. Search in Google Scholar

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, 40-48.10.1016/j.iheduc.2015.12.003 Search in Google Scholar

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), 818-826.10.1016/j.compedu.2010.10.023 Search in Google Scholar

27. Lumsden, L. S. (1994). Student Motivation to Learn. Emergency Librarian, 22(2), 31–32. Search in Google Scholar

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 Search in Google Scholar

29. Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance Education, 26(1), 29-48.10.1080/01587910500081269 Search in Google Scholar

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), n2.10.21432/cjlt27559 Search in Google Scholar

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 Search in Google Scholar

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, 306-317.10.1016/j.compedu.2012.12.014 Search in Google Scholar

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), 182-190.10.4040/jkan.2010.40.2.182 Search in Google Scholar

34. Pechenkina, E., & Aeschliman, C. (2017). What do students want? Making sense of student preferences in technology-enhanced learning. Contemporary Educational Technology, 8(1), 26-39.10.30935/cedtech/6185 Search in Google Scholar

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. Search in Google Scholar

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. Search in Google Scholar

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. Search in Google Scholar

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), 353.10.1037/a0026838 Search in Google Scholar

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 Search in Google Scholar

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).10.19173/irrodl.v5i2.192 Search in Google Scholar

41. Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396-413.10.1016/j.compedu.2005.09.004 Search in Google Scholar

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), 140-147.10.1016/j.nedt.2004.11.004 Search in Google Scholar

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.29707510.17943/etku.297075 Search in Google Scholar

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. Search in Google Scholar

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), 742-748.10.1016/j.compedu.2009.04.014 Search in Google Scholar

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/ Search in Google Scholar

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), 302-323.10.1080/01587919.2013.835779 Search in Google Scholar

48. Ward, B. (2004). The best of both worlds: A hybrid statistics course. Journal of Statistics Education, 12(3).10.1080/10691898.2004.11910629 Search in Google Scholar

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. Search in Google Scholar

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), 1284-1303.10.1016/j.compedu.2006.12.009 Search in Google Scholar

51. Yilmaz, R. (2017). Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom. Computers in Human Behavior, 70, 251-260.10.1016/j.chb.2016.12.085 Search in Google Scholar

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. Search in Google Scholar

53. Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology, 11(4), 307–313.10.1016/0361-476X(86)90027-5 Search in Google Scholar

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