Advertisement

Mathematics Education Research Journal

, Volume 29, Issue 2, pp 237–254 | Cite as

Using expectancy-value theory to explore aspects of motivation and engagement in inquiry-based learning in primary mathematics

  • Jill Fielding-Wells
  • Mia O’Brien
  • Katie Makar
Original Article
First Online:

Abstract

Inquiry-based learning (IBL) is a pedagogical approach in which students address complex, ill-structured problems set in authentic contexts. While IBL is gaining ground in Australia as an instructional practice, there has been little research that considers implications for student motivation and engagement. Expectancy-value theory (Eccles and Wigfield 2002) provides a framework through which children’s beliefs about their mathematical competency and their expectation of success are able to be examined and interpreted, alongside students’ perceptions of task value. In this paper, Eccles and Wigfield’s expectancy-value model has been adopted as a lens to examine a complete unit of mathematical inquiry as undertaken with a class of 9–10-year-old students. Data were sourced from a unit (∼10 lessons) based on geometry and geometrical reasoning. The units were videotaped in full, transcribed, and along with field notes and student work samples, subjected to theoretical coding using the dimensions of Eccles and Wigfield’s model. The findings provide insight into aspects of IBL that may impact student motivation and engagement. The study is limited to a single unit; however, the results provide a depth of insight into IBL in practice while identifying features of IBL that may be instrumental in bringing about increased motivation and engagement of students in mathematics. Identifying potentially motivating aspects of IBL enable these to be integrated and more closely studied in IBL practises.

Keywords

Expectancy-value motivation theory Inquiry-based learning Motivation Engagement Primary mathematics 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

The authors wish to acknowledge the participating students. This work was funded by the ARC grants DP120100690 and DP140101511 and an Australian Postgraduate Award.

References

  1. Australian Academy of Science (AAS). (n.d.). reSolve: Mathematics by Inquiry. Retrieved from https://www.science.org.au/learning/schools/resolve.
  2. Australian Curriculum and Reporting Authority [ACARA]. (2016). Australian curriculum: Mathematics v8.3. Retrieved from http://www.australiancurriculum.edu.au/mathematics/Curriculum/F-10.
  3. Ainley, J., Pratt, D., & Hansen, A. (2006). Connecting engagement and focus in pedagogic task design. British Educational Research Journal, 32(1), 23–38.CrossRefGoogle Scholar
  4. Anderson, R. D. (2002). Reforming science teaching: What research says about inquiry. Journal of Science Teacher Education, 13(1), 1–12.CrossRefGoogle Scholar
  5. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.Google Scholar
  6. Carpenter, T. P., Corbitt, M. K., Kepner, H. S., Lindquist, M. M., & Reys, R. E. (1981). Results from the second mathematics assessment of the National Assessment of educational progress. Reston: National Council of Teachers of Mathematics.Google Scholar
  7. Camenzuli, J., & Buhagiar, M. A. (2014). Using inquiry-based learning to support the mathematical learning of students with SEBD. International Journal of Emotional Education, 6(2), 69–85.CrossRefGoogle Scholar
  8. Cobb, P., Confrey, J., diSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9–13.CrossRefGoogle Scholar
  9. Dweck, C. S. (1998). The development of early self-conceptions: Their relevance for motivational processes. New York: Cambridge University Press.Google Scholar
  10. Eccles, J. S. (2006). A motivational perspective on school achievement. In R. J. Sternberg & R. F. Subotnik (Eds.), Optimizing student success in schools with the other three Rs: reasoning, resilience, and responsibility (pp. 199–224). Greenwich: Information Age Publishing.Google Scholar
  11. Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132.CrossRefGoogle Scholar
  12. Eccles, J. S., Wigfield, A., & Schiefele, U. (1998). Motivation to succeed. In N. Eisenberg (Ed.), Handbook of child psychology (Vol. 3, 5th ed., pp. 1017–1095). New York: Wiley.Google Scholar
  13. Feather, N. T. (1992). Values, valences, expectations, and actions. Journal of Social Issues, 48(2), 109–124. doi: 10.1111/j.1540-4560.1992.tb00887.x.CrossRefGoogle Scholar
  14. Fielding-Wells, J. (2010). Linking problems, conclusions and evidence: Primary students’ early experiences of planning statistical investigations. In C. Reading (Ed.), Proceedings of the 8th international conference on teaching statistics. Voorburg: International Statistical Institute.Google Scholar
  15. Fielding-Wells, J. (2014). Where’s your evidence? Challenging young students’ equiprobability bias through argumentation. In K. Makar, B. de Sousa, & R. Gould (Eds.), International conference on teaching statistics (ICOTS9) Flagstaff, Arizona, USA. Voorburg: International Statistical Institute.Google Scholar
  16. Fielding-Wells, J. (2015). Identifying Core elements of argument-based inquiry in primary mathematics learning. In M. Marshman, V. Geiger, & A. Bennison (Eds.), Mathematics education in the margins (Proceedings of the 38th annual conference of the Mathematics Education Research Group of Australasia). Sunshine Coast: MERGA.Google Scholar
  17. Fielding-Wells, J., & Makar, K. (2008). Student (dis)engagement with mathematics. Paper presented at the Australian Association of Research in Education (AARE), Brisbane, Australia. http://www.aare.edu.au/08pap/mak08723.pdf.
  18. Fielding-Wells, J., & Makar, K. (2012). Developing primary students’ argumentation skills in inquiry-based mathematics classrooms. In K. T. Jan van Aalst, M. J. Jacobson, & P. Reimann (Eds.), The Future of Learning: Proceedings of the 10th International Conference of the Learning Sciences [ICLS 2012]—Volume 2 Short Papers, Symposia, and Abstracts (pp. 149–153). International Society of the Learning Sciences: Sydney.Google Scholar
  19. Fielding-Wells, J., & Makar, K. (2013). Inferring to a model: Using inquiry-based argumentation to challenge young children’s expectations of equally likely outcomes. Paper presented at the the 9th International Conference on Statistical Reasoning, Thinking and Literacy. Superior Shores, MN: SRTL.Google Scholar
  20. Fielding-Wells, J., Dole, S., & Makar, K. (2014). Inquiry pedagogy to promote emerging proportional reasoning in primary students. Mathematics Education Research Journal, 26(1), 1–31.CrossRefGoogle Scholar
  21. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. doi: 10.2307/3516061.CrossRefGoogle Scholar
  22. Greene, B. A., Miller, R. B., Crowson, H. M., Duke, B. L., & Akey, K. L. (2004). Predicting high school students’ cognitive engagement and achievement: contributions of classroom perception and motivation. Contemporary Educational Psychology, 29, 462–482.CrossRefGoogle Scholar
  23. Grolnick, W. S., Gurland, S. T., Jacob, K. F., & Decourcey, W. (2002). The development of self-determination in middle childhood and adolescence. In A. Wigfield & J. S. Eccles (Eds.), The development of achievement motivation (pp. 147–171). Burlington: Elsevier Science.CrossRefGoogle Scholar
  24. Haimovitz, K., & Dweck, C. S. (2016). What predicts children’s fixed and growth intelligence mind-sets? Not their parents’ views of intelligence but their parents’ views of failure. Psychological Science, 27(6), 859–869. doi: 10.1177/0956797616639727.CrossRefGoogle Scholar
  25. Kogan, M., & Laursen, S. L. (2014). Assessing long-term effects of inquiry-based learning: A case study from college mathematics. Innovative Higher Education, 39(3), 183–199. doi: 10.1007/s10755-013-9269-9.CrossRefGoogle Scholar
  26. Kong, Q., Wong, N., & Lam, C. (2003). Student engagement in mathematics: Development of instrument and validation of construct. Mathematics Education Research Journal, 15(1), 4–21.CrossRefGoogle Scholar
  27. Makar, K. (2012). The pedagogy of mathematics inquiry. In R. M. Gillies (Ed.), Pedagogy: New developments in the learning sciences (pp. 371–397). New York: Nova Science Publishers.Google Scholar
  28. Makar, K., & Fielding-Wells, J. (2011). Teaching teachers to teach statistical investigations. In C. Batanero, G. Burrill, & C. Reading (Eds.), Teaching statistics in school mathematics-challenges for teaching and teacher education Vol. 14 (pp. 347–358). Dordrecht: Springer.Google Scholar
  29. Martin, A. J. (2012). Part II commentary: motivation and engagement: conceptual, operational, and empirical clarity. In A. Christenson, A. Reschly, & C. White (Eds.), Handbook of research on student engagement (pp. 303–311). New York: Springer.CrossRefGoogle Scholar
  30. McGregor, D. (2016). Exploring the impact of inquiry based learning on students’ beliefs and attitudes towards mathematics. Paper presented at the 38th Annual Conference of the Mathematics Education Research Group of Australasia. Adelaide: Australia.Google Scholar
  31. Minsky, M. (1961). Steps toward artificial intelligence. Proceedings of the IRE, 49(1), 8–30. doi: 10.1109/JRPROC.1961.287775.CrossRefGoogle Scholar
  32. NCTM. (1989). Curriculum and Evaluation Standards for School Mathematics. National Council of Teachers of Mathematics. Reston: NCTM.Google Scholar
  33. Newman, R. S. (2002). What do I need to do to succeed… when I don’t understand what I’m doing!?: developmental influences on students’ adaptive help seeking. In A. Wigfield & J. S. Eccles (Eds.), The development of achievement motivation (pp. 285–306). Burlington: Elsevier Science.CrossRefGoogle Scholar
  34. Ormrod, J. E. (2006). Educational Psychology (5th ed.). Upper Saddle River, NJ: Pearson/Merrill Prentice Hall.Google Scholar
  35. Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667–686. doi: 10.1037/0022-0663.95.4.667.CrossRefGoogle Scholar
  36. Pintrich, P. R., Marx, R. W., & Boyle, R. A. (1993). Beyond cold conceptual change: the role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63(2), 167–199.CrossRefGoogle Scholar
  37. Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Columbus: Merrill Prentice Hall.Google Scholar
  38. Powell, A. B., Francisco, J. M., & Maher, C. A. (2003). An analytical model for studying the development of learners' mathematical ideas and reasoning using videotape data. The Journal of Mathematical Behavior, 22(4), 405–435.CrossRefGoogle Scholar
  39. Reitman, W. R. (1965). Cognition and thought: an information processing approach. New York: Wiley.Google Scholar
  40. Sandoval, W. A., & Millwood, K. A. (2007). What can argumentation tell us about epistemology? In S. Erduran & M. P. Jimenez-Aleixandre (Eds.), Argumentation in science education (pp. 71–88). Dordrecht: Springer.Google Scholar
  41. Schunk, D. H., & Mullen, C. A. (2012). Self-efficacy as an engaged learner. In A. Christenson, A. Reschly, & C. White (Eds.), Handbook of research on student engagement (pp. 219–235). New York: Springer.CrossRefGoogle Scholar
  42. Simon, H. A. (1973). The structure of ill-structured problems. Artificial Intelligence, 4(3–4), 181–201.CrossRefGoogle Scholar
  43. Skilling, K., Bobis, J., & Martin, A. (2015). The engagement of students with high and low achievement levels in mathematics. In K. Beswick, T. Muir, & J. Fielding-Wells (Eds.), Proceedings of the 39 th Psychology of Mathematics Education Conference (Vol. 4, pp. 185–192). Hobart: PME.Google Scholar
  44. Wigfield, A., Eccles, J. S., Fredricks, J. A., Simpkins, S., Roeser, R. W., & Schiefele, U. (2015). Development of achievement motivation and engagement. In R. M. Lerner & M. E. Lamb (Eds.), Handbook of child psychology and developmental science (Vol. 3, pp. 657–701). New York: Wiley.Google Scholar
  45. Wigfield, A., Eccles, J. S., Schiefele, U., Roeser, R., & Davis-Kean, P. (2006). Development of achievement motivation. In W. Damon & N. Eisenberg (Eds.), Handbook of child psychology (Vol. 3, pp. 933–1002). New York: Wiley.Google Scholar

Copyright information

© Mathematics Education Research Group of Australasia, Inc. 2017

Authors and Affiliations

  1. 1.The University of QueenslandSt LuciaAustralia
  2. 2.Griffith UniversityNathanAustralia

Personalised recommendations

Cite article

Buy options