Advertisement

Technology, Knowledge and Learning

, Volume 21, Issue 2, pp 243–253 | Cite as

The Development of a Self-regulation in a Collaborative Context Scale

  • Victor Law
  • Xun Ge
  • Deniz Eseryel
Article

Abstract

Self-regulation has been shown as a critical factor in learning in a regular classroom environment (e.g. Wolters and Pintrich in Instr Sci 26(1):27–47, 1998. doi: 10.1023/A:1003035929216). However, little research has been conducted to understand self-regulation in the context of collaboration (Dinsmore et al. in Educ Psychol Rev 20(4):391–409, 2008. doi: 10.1007/s10648-008-9083-6). Recently, researchers have been exploring how learners regulate themselves in collaborative problem-solving environments using qualitative methods (e.g. Chan in Metacogn Learn 7(1):63–73, 2012. doi: 10.1007/s11409-012-9086-z; Lajoie and Lu in Metacogn Learn, 2011. doi: 10.1007/s11409-011-9077-5). However, there is a lack of instruments to measure self-regulation in a collaborative context (SRCC). Therefore, the current study was intended to propose a new instrument to measure SRCC. One hundred and thirty-one college students from a Midwestern university completed a survey for SRCC after participating in a collaborative problem-solving task. The exploratory factor analysis yielded four factors: clarification and resolution, elaboration, refuting, and summarization. Three of the four factors were moderately correlated. The results contribute to our understanding of self-regulation in a collaborative context, which allows researchers to study this phenomenon quantitatively.

Keywords

Self-regulation Collaborative learning Ill-structured problem solving Exploratory factor analysis 

References

  1. Alexander, P. A. (1995). Superimposing a situation-specific and domain-specific perspective on an account of self-regulated learning. Educational Psychologist, 30(4), 189–193. doi: 10.1207/s15326985ep3004_3.CrossRefGoogle Scholar
  2. Azevedo, R., Cromley, J. G., & Seibert, D. (2004). Does adaptive scaffolding facilitate students’ ability to regulate their learning with hypermedia? Contemporary Educational Psychology, 29(3), 344–370. doi: 10.1016/j.cedpsych.2003.09.002.CrossRefGoogle Scholar
  3. Boekaerts, M. (1997). Self-regulated learning: A new concept embraced by researchers, policy makers, educators, teachers, and students. Learning and Instruction, 7(2), 161–186. doi: 10.1016/S0959-4752(96)00015-1.CrossRefGoogle Scholar
  4. Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245–281. doi: 10.3102/00346543065003245.CrossRefGoogle Scholar
  5. Chan, C. K. K. (2012). Co-regulation of learning in computer-supported collaborative learning environments: A discussion. Metacognition and Learning, 7(1), 63–73. doi: 10.1007/s11409-012-9086-z.CrossRefGoogle Scholar
  6. Chiu, M. M., & Kuo, S. W. (2009). From metacognition to social metacognition. Journal of Education Research, 3(4), 321–338.Google Scholar
  7. Cho, M.-H., & Jonassen, D. (2009). Development of the human interaction dimension of the self-regulated learning questionnaire in asynchronous online learning environments. Educational Psychology, 29(1), 117–138. doi: 10.1080/01443410802516934.CrossRefGoogle Scholar
  8. Dabbagh, N., & Kitsantas, A. (2005). Using web-based pedagogical tools as scaffolds for self-regulated learning. Instructional Science, 33(5), 513–540. doi: 10.1007/s11251-005-1278-3.CrossRefGoogle Scholar
  9. Dinsmore, D., Alexander, P., & Loughlin, S. (2008). Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educational Psychology Review, 20(4), 391–409. doi: 10.1007/s10648-008-9083-6.CrossRefGoogle Scholar
  10. Efklides, A. (2008). Metacognition: Defining its facets and levels of functioning in relation to self-regulation and co-regulation. European Psychologist, 13(4), 277–287. doi: 10.1027/1016-9040.13.4.277.CrossRefGoogle Scholar
  11. Fawcett, L. M., & Garton, A. F. (2005). The effect of peer collaboration on children’s problem-solving ability. British Journal of Educational Psychology, 75(2), 157–169. doi: 10.1348/000709904x23411.CrossRefGoogle Scholar
  12. Ge, X. (2001). Scaffolding students’ problem-solving processes in an ill-structured task using question prompts and peer interactions. (Ph.D. Doctoral Dissertation), The Pennsylvania State University, State College, PA.Google Scholar
  13. Ge, X., & Land, S. (2003). Scaffolding students’ problem-solving processes in an ill-structured task using question prompts and peer interactions. Educational Technology Research and Development, 51(1), 21–38. doi: 10.1007/BF02504515.CrossRefGoogle Scholar
  14. Ge, X., & Land, S. M. (2004). A conceptual framework for scaffolding iii-structured problem-solving processes using question prompts and peer interactions. Educational Technology Research and Development, 52(2), 5–22. doi: 10.1007/BF02504836.CrossRefGoogle Scholar
  15. Gick, M. L. (1986). Problem-solving strategies. Educational Psychologist, 21(1), 99–120. doi: 10.1207/s15326985ep2101&2_6.CrossRefGoogle Scholar
  16. Goos, M., Galbraith, P., & Renshaw, P. (2002). Socially mediated metacognition: Creating collaborative zones of proximal development in small group problem solving. Educational Studies in Mathematics, 49(2), 193–223. doi: 10.1023/a:1016209010120.CrossRefGoogle Scholar
  17. Greene, J. A., Hutchison, L. A., Costa, L.-J., & Crompton, H. (2012). Investigating how college students’ task definitions and plans relate to self-regulated learning processing and understanding of a complex science topic. Contemporary Educational Psychology,. doi: 10.1016/j.cedpsych.2012.02.002.Google Scholar
  18. Hadwin, A. F., Oshige, M., Gress, 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. doi: 10.1016/j.chb.2007.06.007.CrossRefGoogle Scholar
  19. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson.Google Scholar
  20. Hurme, T.-R., Merenluoto, K., & Järvelä, S. (2009). Socially shared metacognition of pre-service primary teachers in a computer-supported mathematics course and their feelings of task difficulty: A case study. Educational Research and Evaluation, 15(5), 503–524. doi: 10.1080/13803610903444659.CrossRefGoogle Scholar
  21. Iiskala, T., Vauras, M., Lehtinen, E., & Salonen, P. (2011). Socially shared metacognition of dyads of pupils in collaborative mathematical problem-solving processes. Learning and Instruction, 21(3), 379–393. doi: 10.1016/j.learninstruc.2010.05.002.CrossRefGoogle Scholar
  22. Järvelä, S., & Järvenoja, H. (2011). Socially constructed self-regulated learning and motivation regulation in collaborative learning groups. Teachers College Record, 113(2), 350–374.Google Scholar
  23. Järvelä, S., Järvenoja, H., & Veermans, M. (2008). Understanding the dynamics of motivation in socially shared learning. International Journal of Educational Research, 47(2), 122–135. doi: 10.1016/j.ijer.2007.11.012.CrossRefGoogle Scholar
  24. Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research on motivation in collaborative learning: Moving beyond the cognitive–situative divide and combining individual and social processes. Educational Psychologist, 45(1), 15–27. doi: 10.1080/00461520903433539.CrossRefGoogle Scholar
  25. Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65–94. doi: 10.1007/BF02299613.CrossRefGoogle Scholar
  26. Kramarski, B., & Gutman, M. (2006). How can self-regulated learning be supported in mathematical E-learning environments? Journal of Computer Assisted learning, 22(1), 24–33. doi: 10.1111/j.1365-2729.2006.00157.x.CrossRefGoogle Scholar
  27. Lajoie, S., & Lu, J. (2011). Supporting collaboration with technology: Does shared cognition lead to co-regulation in medicine? Metacognition and Learning. doi: 10.1007/s11409-011-9077-5.Google Scholar
  28. Manlove, S., Lazonder, A. W., & de Jong, T. (2006). Regulative support for collaborative scientific inquiry learning. Journal of Computer Assisted learning, 22(2), 87–98. doi: 10.1111/j.1365-2729.2006.00162.x.CrossRefGoogle Scholar
  29. McCaslin, M. (2009). Co-regulation of student motivation and emergent identity. Educational Psychologist, 44(2), 137–146. doi: 10.1080/00461520902832384.CrossRefGoogle Scholar
  30. OECD. (2013). PISA 2015. Draft collaborative problem solving framework. Retrieved from http://www.oecd.org/pisa/pisaproducts/Draft%20PISA%202015%20Collaborative%20Problem%20Solving%20Framework%20.pdf.
  31. Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). San Diego, CA: Academic Press.CrossRefGoogle Scholar
  32. Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). Ann Arbor, MI: University of Michigan.Google Scholar
  33. Shin, N., Jonassen, D. H., & McGee, S. (2003). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching, 40(1), 6–33. doi: 10.1002/tea.10058.CrossRefGoogle Scholar
  34. Sinnott, J. D. (1989). A model for solution of ill-structured problems: Implications for everyday and abstract problem solving. In J. D. Sinnott (Ed.), Everyday problem solving: Theory and application (pp. 72–99). New York, NY: Praeger.Google Scholar
  35. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Needham Heights, MA: Allyn & Bacon.Google Scholar
  36. Teasley, S. D., & Roschelle, J. (1993). Constructing a joint problem space: The computer as a tool for sharing knowledge. In S. Derry & S. Lajoie (Eds.), Computers as cognitive tools (pp. 229–257). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  37. Volet, S., & Mansfield, C. (2006). Group work at university: Significance of personal goals in the regulation strategies of students with positive and negative appraisals. Higher Education Research & Development, 25, 341–356. doi: 10.1080/07294360600947301.CrossRefGoogle Scholar
  38. Volet, S., Summers, M., & Thurman, J. (2009). High-level co-regulation in collaborative learning: How does it emerge and how is it sustained? Learning and Instruction, 19(2), 128–143. doi: 10.1016/j.learninstruc.2008.03.001.CrossRefGoogle Scholar
  39. Voss, J. F., & Post, T. A. (1988). On the solving of ill-structured problems. In M. T. H. Chi & R. Glaser (Eds.), The nature of expertise (pp. 261–285). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  40. Webb, M., & Gibson, D. (2015). Technology enhanced assessment in complex collaborative settings. Education and Information Technologies, 20(4), 675–695. doi: 10.1007/s10639-015-9413-5.CrossRefGoogle Scholar
  41. Whipp, J. L., & Chiarelli, S. (2004). Self-regulation in a web-based course: A case study. Educational Technology Research and Development, 52(4), 5–22.CrossRefGoogle Scholar
  42. Winne, P. H. (2010). Improving measurements of self-regulated learning. Educational Psychologist, 45(4), 267–276. doi: 10.1080/00461520.2010.517150.CrossRefGoogle Scholar
  43. Wolters, C. A., & Pintrich, P. R. (1998). Contextual differences in student motivation and self-regulated learning in mathematics, English, and social studies classrooms. Instructional Science, 26(1), 27–47. doi: 10.1023/A:1003035929216.CrossRefGoogle Scholar
  44. Zhang, J., Chen, Q., Sun, Y., & Reid, D. J. (2004). Triple scheme of learning support design for scientific discovery learning based on computer simulation: Experimental research. Journal of Computer Assisted Learning, 20(4), 269–282. doi: 10.1111/j.1365-2729.2004.00062.x.CrossRefGoogle Scholar
  45. Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3–17.CrossRefGoogle Scholar
  46. Zimmerman, B. J. (2001). Theories of self-regulated learning and academic achievement: An overview and analysis. In B. J. Zimmerman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (pp. 1–37). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Program of Organization, Information, and Learning SciencesUniversity of New MexicoAlbuquerqueUSA
  2. 2.Department of Educational Psychology, Jeannine Rainbolt College of EducationUniversity of OklahomaNormanUSA
  3. 3.College of EducationNorth Carolina State UniversityRaleighUSA

Personalised recommendations