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Journal of Computing in Higher Education

, Volume 31, Issue 2, pp 408–425 | Cite as

Learning engagement via promoting situational interest in a blended learning environment

  • Yan Keung HuiEmail author
  • Chen Li
  • Sheng Qian
  • Lam For Kwok
Article

Abstract

In educational psychology, the theories of interest and self-determination have been well studied to find the relationships between learning attitudes and learning outcomes. However, the instructional design and the learning behaviors are the two missing elements which have not been fully investigated in the learning process. Therefore, we conducted two studies longitudinally with 2 years data from a 13-week engineering course at the City University of Hong Kong in a blended learning environment to verify the criticalness of these elements in these studies. With engagement records being collected from the learning management system in the second year, we further correlated the relationship from situational interest to engaged learning and finally the academic performance. Our findings make theoretical contributions by combining these two theories and link the model with behavior and achievement of students. It also demonstrates the importance of these theories on the instructional design.

Keywords

Situational interest Theory of interest Self-determination theory Instructional design 

Notes

References

  1. Ainley, M. (2012). Students’ interest and engagement in classroom activities. In S. Christenson, A. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 283–302). Boston, MA: Springer.CrossRefGoogle Scholar
  2. Arnone, M. P., Small, R. V., Chauncey, S. A., & McKenna, H. P. (2011). Curiosity, interest and engagement in technology pervasive learning environments: A new research agenda. Edu-cational Technology Research and Development, 59(2), 181–198.CrossRefGoogle Scholar
  3. Bomia, L., Beluzo, L., Demeester, D., Elander, K., Johnson, M., & Sheldon, B. (1997). The impact of teaching strategies on intrinsic motivation, Champaign. IL: ERIC Clearinghouse on Elementary and Early Childhood Education.Google Scholar
  4. Cenfetelli, R. T., & Bassellier, G. (2009). Interpretation of formative measurement in information systems research. MIS Quarterly, 33(4), 689–707.CrossRefGoogle Scholar
  5. Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), VII–XVI.Google Scholar
  6. Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.CrossRefGoogle Scholar
  7. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, New Jersey: Erlbaum Associates.Google Scholar
  8. Deci, E. L. (1975). Intrinsic motivation. New York: Plenum Press.CrossRefGoogle Scholar
  9. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.CrossRefGoogle Scholar
  10. Deci, E. L., & Ryan, R. M. (1994). Promoting self-determined education. Scandinavian Journal of Educational Research, 38(1), 3–14.CrossRefGoogle Scholar
  11. Deci, E. L., & Ryan, R. M. (2002). Overview of self-determination theory: An organismic dialectical perspective. In E. L. Deci & R. M. Ryan (Eds.), Handbook of self-determination research (pp. 3–33). Rochester: University of Rochester Press.Google Scholar
  12. Dewey, J. (2009). Interest and effort in education. Carbondale: Southern Illinois University Press.Google Scholar
  13. Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LIS-REL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440–452.CrossRefGoogle Scholar
  14. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRefGoogle Scholar
  15. Gefen, D., Rigdon, E. E., & Straub, D. W. (2011). An update and extension to SEM guidelines for administrative and social science research. MIS Quarterly, 35(2), iii–xiv.CrossRefGoogle Scholar
  16. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. A. (2014). Primer on partial least squares: Structural equation modeling (PLS-SEM). Los Angeles: Sage Publications.Google Scholar
  17. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.CrossRefGoogle Scholar
  18. Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.CrossRefGoogle Scholar
  19. Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., et al. (2014). Common beliefs and reality about partial least squares: Comments on Ronkko & Evermann (2013). Organizational Research Methods, 17(2), 182–209.CrossRefGoogle Scholar
  20. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.CrossRefGoogle Scholar
  21. Hoffmann, L., Krapp, A., Renninger, K. A., & Baumert, J. (1998). Interest and learning. In Proceedings of the Seeon conference on interest and learning. Kiel: IPN.Google Scholar
  22. Hui, Y. K., Li, C., Qian, S., & Kwok, L. (2018). Cultivating situational interest in blended learning environment. In S. K. S. Cheung, L. Kwok & K. Kubota (Eds.), Blended learning: Enhancing learning success, 11th international conference, ICBL 2018 (lecture notes in computer science) (Vol. 10949, pp. 81–92). Springer.Google Scholar
  23. Hui, Y. K., Mai, B., Qian, S., & Kwok, L. F. (2018b). Cultivating better learning attitudes: A preliminary longitudinal study. Open Learning, 33(2), 155–170.CrossRefGoogle Scholar
  24. Hung, D., Tan, S. C., & Koh, T. S. (2006). Engaged learning: Making learning an authentic experience. In D. Hung & M. S. Khine (Eds.), Engaged learning with emerging technology (pp. 29–48). Dordrecht: Springer.CrossRefGoogle Scholar
  25. Klein, H. J., Noe, R. A., & Wang, C. W. (2006). Motivation to learn and course outcomes: The impact of delivery mode, learning goal, orientation, and perceived barriers and enablers. Personnel Psychology, 59(3), 665–702.CrossRefGoogle Scholar
  26. Krapp, A. (2002). An educational psychological theory of interest and its relation to SDT. In E. L. Deci & R. M. Ryan (Eds.), Handbook on self-determination research (pp. 405–427). Rochester: University of Rochester Press.Google Scholar
  27. Muller, F., & Louw, J. (2004). Learning environment, motivation and interest: Perspectives on self-determination theory. South African Journal of Psychology, 34(2), 169–190.CrossRefGoogle Scholar
  28. Newmann, F. (1992). Student engagement and achievement in American Secondary Schools, New York. NY: Teachers College Press.Google Scholar
  29. Pintrich, P. R., Smith, D. A. F., Duncan, T., & Mckeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ).Google Scholar
  30. Rheinberg, F., Vollmeyer, R., & Burns, B. D. (2000). Motivation and self-regulated learning. Pattern Recognition, 131(1), 81–108.Google Scholar
  31. Rotgans, J. I., & Schmidt, H. G. (2011). Situational interest and academic achievement in active-learning classroom. Learning and Instruction, 21(1), 58–67.CrossRefGoogle Scholar
  32. Shi, X., Lin, Z., Liu, J., & Hui, Y. K. (2018). Consumer loyalty toward smartphone brands: The determining roles of deliberate inertia and cognitive lock-in. Information & Management, 55(7), 866–876.CrossRefGoogle Scholar
  33. Urban-Woldron, H., & Hopf, M. (2011). TPACK—a prerequisite for successful technology integration into the classroom? In W. Kaminski, M.-P. Larvor, & G. Mary (Eds.), Teaching and learning physics today.Google Scholar
  34. Wang, M., & Kang, M. (2006). Cybergogy for engaged learning: A framework for creating learner engagement through information and communication technology. In D. Hung & M. S. Khine (Eds.), Engaged learning with emerging technologies (pp. 225–253). Dordrecht: Springer.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceCity University of Hong KongKowloonHong Kong

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