Understanding student pathways in context-rich problems
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This paper describes the ways that students’ problem-solving behaviors evolve when solving multi-faceted, context-rich problems within a web-based learning environment. During the semester, groups of two or three students worked on five physics problems that required drawing on more than one concept and, hence, could not be readily solved with simple “plug-and-chug” strategies. The problems were presented to students in a data-rich, online problem-based learning environment that tracked which information items were selected by students as they attempted to solve the problem. The students also completed a variety of tasks, like entering an initial qualitative analysis of the problem into an online form. Students were not constrained to complete these tasks in any specific order. As they gained more experience in solving context-rich physics problems, student groups showed some progression towards expert-like behavior as they completed qualitative analysis earlier and were more selective in their perusal of informational resources. However, there was room for more improvement as approximately half of the groups still completed the qualitative analysis task towards the end of the problem-solving process rather than at the beginning of the task when it would have been most useful to their work.
- Baker, E. L., & O’Neil, H. F. (2002). Measuring problem solving in computer environments: current and future states. Computers in Human Behavior, 18, 609–622. CrossRef
- Bereiter, C., & Scardamalia, M. (1993). Surpassing ourselves: An inquiry into the nature and implications of expertise. Chicago: Open Court Publishing.
- Bunce, D. M., & Heikkinen, H. (1986). The effects of an explicit problem-solving approach on mathematical chemistry achievement. Journal of Research in Science Teaching, 23, 11. CrossRef
- Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152. CrossRef
- Chung, G. & Baker, E. L. (2002). An exploratory study to examine the feasibility of measuring problem-solving processes using a click-through interface. Journal of Technology, Learning and Assessment, 2(2).
- Cognition and Technology Group at Vanderbilt. (1992). The Jasper experiment: an exploration of issues in learning and instructional design. Educational Technology Research and Development, 40, 65. CrossRef
- Dufresne, R. J., Gerace, W. J., Hardiman, P. T., & Mestre, J. P. (1992). Constraining novices to perform expertlike problem analyses: effects on schema acquisition. Journal of the Learning Sciences, 2, 307. CrossRef
- Gabel, D. (1993). Handbook of research on science teaching and learning. New York: Macmillan.
- Halloun, I. A., & Hestenes, D. (1986). Modeling instruction in mechanics. American Journal of Physics, 55, 455–462. CrossRef
- Heller, P., Keith, R., & Anderson, S. (1992). Teaching problem solving through cooperative grouping. Part 1: group versus individual problem solving. American Journal of Physics, 60, 627. CrossRef
- Hurst, R. W., & Milkent, M. M. (1996). Facilitating successful prediction problem solving in biology through application of skill theory. Journal of Research in Science Teaching, 33, 541–552. CrossRef
- Jonassen, D. H. (2004). Learning to solve problems: An instructional design guide. Pfeiffer Publishing.
- King, P. M., & Kitchener, K. S. (1994). Developing reflective judgment: Understanding and promoting intellectual growth and critical thinking in adolescents and adults. San Franscisco: Jossey-Bass.
- Leonard, W. J., Dufresne, R. J., & Mestre, J. P. (1996). Using qualitative problem-solving strategies to highlight the role of conceptual knowledge in solving problems. American Journal of Physics, 64, 1495. CrossRef
- Mazur, E. (1997). Peer instruction: A user’s manual. Series in educational innovation. Upper Saddle River: Prentice Hall.
- McDermott, L., & Schaffer, P. S. (2002). Tutorials in introductory physics. Upper Saddle River: Prentice Hall.
- Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. Cambridge: Cambridge University Press.
- Olafsson, S., Huba, M., Jackman, J., Peters, F., & Ryan, S. (2003). Information technology based active learning: a pilot study for engineering economy. In Proceedings of the 2003 American Society for Engineering Education Annual Conference, June 22–25, Nashville, TN.
- Olafsson, S., Saunders, K., Jackman, J., Peters, F., Ryan, S., Dark, V. et al. (2004). Implementation and assessment of industrial engineering curriculum reform. In Proceedings of the 2004 American Society for Engineering Education Annual Conference, June 20–23, Salt Lake City, UT.
- Polya, G. (1957). How to solve it. New Jersey: Princeton University Press.
- Reid, N., & Yang, M.-J. (2002). Open-ended problem-solving in school chemistry: a preliminary investigation. International Journal of Science Education, 24, 1313–1332. CrossRef
- Reif, F., Larkin, J. H., & Brackett, G. C. (1976). Teaching general learning and problem-solving skills. American Journal of Physics, 44, 212–217. CrossRef
- Rose, C. P. (2006). Private communication.
- Ryan, S., Jackman, J., Peters, F., Olafsson, S., & Huba, M. (2004). The engineering learning portal for problem solving: experience in a large engineering economy class. The Engineering Economist, 49, 1–20. CrossRef
- Ryan, S. Jackman, J., Marathe, R., Antonenko, P., Kumsaikaew, P., Niederhauser, D., et al. (2007). Student selection of information relevant to solving ill-structured engineering economic decision problems. In Proceedings of the 2007 American Society for Engineering Education Annual Conference, June 24–27, Honolulu.
- Savelsbergh, E., de Jong, T., & Ferguson-Hessler, M. G. M. (2002). Situational knowledge in physics: the case of electrodynamics. Journal of Research in Science Teaching, 39, 928. CrossRef
- Schoenfeld, A. (1985). Mathematical problem solving. London: Academic.
- Stevens, R., & Palacio-Cayetano, J. (2003). Design and performance frameworks for constructing problem-solving simulations. Cell Biology Education, 2, 162. CrossRef
- Stevens, R., Ikeda, J., & Casillas, A. (1999). Artificial neural network-based performance assessments. Computers in Human Behavior, 15, 295–313. CrossRef
- Stevens, R., Soller, A., Cooper, M., & Sprang, M. (2004). Modeling the development of problem solving skills in chemistry with a web-based tutor. Lecture Notes in Computer Science, 3220, 580. Springer-Verlag, Heidelberg, Germany. CrossRef
- Taconis, R., & Hout-Wolters, B. (1999). Systematic comparison of solved problems as a cooperative learning task. Research in Science Education, 29, 313. CrossRef
- Van Heuvelen, A. (1991). Overview, case study physics. American Journal of Physics, 59, 898. CrossRef
- VanLehn, K. (2005). Private communication.
- Xun, G. E., & Land, S. M. (2004). A conceptual framework for scaffolding ill-structured problem-solving processes using question prompts and peer interactions. Educational Technology Research and Development, 52, 5. CrossRef
- Understanding student pathways in context-rich problems
Education and Information Technologies
Volume 16, Issue 4 , pp 323-342
- Cover Date
- Print ISSN
- Online ISSN
- Springer US
- Additional Links
- Problem solving
- Physics education
- Expertise development
- Click stream analysis
- Learning portal
- Author Affiliations
- 1. Oklahoma State University, Stillwater, OK, 74078, USA
- 2. Iowa State University, Ames, IA, 50011, USA
- 3. Bangkok Bank, PCL, Bangkok, 10500, Thailand
- 4. Indian Institute of Technology Madras, Chennai, 600 036, India