Abstracts
Abstract
Previous studies have described many scales for measuring self-regulation; however, no scale has been developed specifically for self-paced open and distance learning environments. Therefore, the aim of this study is to develop a scale for determining the self-regulated learning skills of distance learners in self-paced open and distance learning courses. Participants of this study were 1279 distance learners who were part of self-paced distance learning courses in a public open and distance teaching university in Turkey. The items of the scale were prepared based on the literature review, expert opinions, and learner questionnaires. The items of the scale were reduced from 62 to 30 after expert opinions and validity and reliability analyses. For the validity of the scale, the exploratory and confirmatory factor analyses were conducted. The total variance was found to be 58.204%. The Cronbach’s alpha coefficient calculated for the reliability of the scale was found to be .937. Five factors composed of goal setting, help seeking, self-study strategies, managing physical environment, and effort regulation emerged in the 30-item scale. Thus, it was concluded that the scale has a high validity and reliability. This scale is intended to help teachers and instructional designers in developing strategies that will enable learners to either enhance their existing self-regulated learning skills or help them to acquire new skills in self-paced open and distance learning environments.
Keywords:
- self-regulated learning,
- self-paced open and distance learning,
- flexible learning,
- independent learning,
- autonomous learners
Appendices
Bibliography
- Anderson, T., Annand, D., & Wark, N. (2005). The search for learning community in learner paced distance education: Or, 'Having your cake and eating it, too!' Australasian Journal of Educational Technology, 21(2), 222-241.
- Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students' learning with hypermedia? Journal of Educational Psychology, 96(3), 523-535.
- Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S.-L. (2009). Measuring self-regulation in online and blended learning environments. The Internet and Higher Education, 12(1), 1-6.
- Barnard-Brak, L., Lan, W. Y., & Paton, W. O. (2010). Profiles in self-regulated learning in the online learning environment. International Review of Research in Open and Distance Learning, 11(1), 61-80.
- Bergamin, P.B., Werlen, E., Siegenthaler, E., & Ziska, S. (2012). The relationship between flexible and self-regulated learning in open and distance universities. International Review of Research in Open and Distributed Learning, 13(2), 101-123.
- Brown, J. M., Miller, W. R., & Lawendowski, L. A. (1999). The self-regulation questionnaire. In L. Vande Creek & T.L. Jackson (Eds.), Innovations in clinical practice: A sourcebook (pp.281-292). Sarasota, FL: Professional Resource Press/Professional Resource Exchange.
- Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245-281.
- Buyukozturk, S. (2009). Sosyal bilimler için veri analizi el kitabı [Handbook of data analysis for social sciences]. Ankara: Pegem Akademi.
- Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309.
- Cokluk, O., Sekercioglu, G., & Buyukozturk, S. (2010). Sosyal bilimler için çok değişkenli istatistik [Multivariate statistics for social sciences]. Pegem Akademi: Ankara.
- Dabbagh, N., & Kitsantas, A. (2005). Using web-based pedagogical tools as scaffolds for self-regulated learning. Instructional Science, 33, 513-540.
- Dabbagh, N., & Kitsantas, A. (2009). Exploring how experienced online instructors use integrative learning technologies to support self-regulated learning. International Journal of Technology in Teaching and Learning, 5(2), 154-168.
- Dabbagh N., & Kitsantas, A. (2012). Personal learning environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. Internet and Higher Education, 15, 3-8.
- Daniel, J. S. (1996). Mega-universities and knowledge media: Technology strategies for higher education. Brighton: Psychology Press.
- edX. (2018). Differences between instructor- and self-paced courses [Blog post]. Retrieved from http://edx.readthedocs.io/projects/edx-guide-for-students/en/latest/SFD_self_paced.html
- Ferguson, F., & Takane, Y. (1989). Statistical analysis in psychology and education. New-York: McGraw Hill Book Company.
- Garrison, R. (2000). Theoretical challenges for distance education in the 21st century: A shift from structural to transactional issues. International Review of Research in Open and Distributed Learning, 1(1), 1-17.
- Guadagnoli, E., & Velicer, W. F. (1988). Relation to sample size to the stability of component patterns. Psychological Bulletin, 103(2), 265.
- Hadwin, A. F., Oshige, M., Gres, C. L. Z., & Winne, P. H. (2010). Innovative ways for using gStudy to orchestrate and research social aspects of self-regulated learning. Computers in Human Behavior, 26(5), 794-805.
- Koçdar, S. (2015). Çevrimiçi ortamlarda öğrenenlerin öz-yönetim becerilerinin geliştirilmesinde kullanılan stratejiler ve araçlar [Strategies and tools used for developing self-regulated skills of learners in online environments]. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 1(1), 39-55.
- Kuo, Y. C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. Internet and Higher Education, 20, 35-50.
- Lehmann, T., Hähnlein, I., & Ifenthaler, D. (2014). Cognitive, metacognitive and motivational perspectives on preflection in self-regulated online learning. Computers in Human Behavior, 32, 313-323.
- 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.
- Milligan, C., Littlejohn, A., & Margaryan, A. (2013). Patterns of engagement in connectivist MOOCs. Journal of Online Learning and Teaching, 9(2), 149.
- Moore, M. G., & Kearsley, G. (2012). Distance education: A systems view of online learning. Belmont, CA: Wadsworth-Cengage Learning.
- Naidu, S. (2008). Enabling time, pace, and place independence. In J. M. Spector, M. D. Merill, J. Merrienboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (pp.259-268). New York: Lawrence Erlbaum Associates.
- Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), The handbook of self-regulation: Theory, research, and applications (pp. 451-502). San Diego: Academic.
- Pintrich, P. R., Smith, D. A., Garcia, T., & McKeachie W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ, NCRIPTAL-91-B-004). Retrieved from National Center for Research to Improve Postsecondary Teaching and Learning. Ann Arbor, University of Michigan website: https://files.eric.ed.gov/fulltext/ED338122.pdf
- Scherer, R. F. (1988). Dimensionality of coping: Factor stability using the ways of coping questionnaire. Psychological Report, 62,76-770.
- Schermelleh-Engel, K., & Moosbrugger, H., (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
- Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. Chichester, United Kingdom: John Wiley & Sons.
- Tavsancil, E. (2014). Tutumların ölçülmesi ve SPSS ile veri analizi [Measuring attitudes and data analysis with SPSS]. Ankara: Nobel.
- Weinstein, C. E., Palmer, D. R., & Acee, T.W. (2016). LASSI: User's manual learning and study strategies inventory. Clearwater, FL: H&H Publishing Company, Inc.
- Whipp, J. L., & Chiarelli, S. (2004). Self-regulation in a web-based course: A case study. Educational Technology Research & Development, 52(4), 5-22.
- Wilson, J. (1997). Self-regulated learners and distance education theory [Electronic document]. Retrieved from http://etad.usask.ca/802papers/wilson/wilson.html
- Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Educational Technology & Society, 10(2), 71-83.
- Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & Moshe Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). New York: Academic.
- Zimmerman, B. J., & Risemberg R. (1997). Self-regulatory dimensions of academic learning and motivation. In G. D. Phye (Ed.), Handbook of academic Learning: Construction of knowledge (pp. 105-125). San Diego, CA: Academic.
- Zimmerman, B. J., & Schunk, D. H. (1989). Self-regulated learning and academic achievement: Theory, research, and practice. New York: Springer-Verlag.