Supporting Problem Solving in PBL

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David Jonassen


Although the characteristics of PBL (problem focused, student centered, self-directed, etc.) are well known, the components of a problem-based learning environment (PBLE) and the cognitive scaffolds necessary to support learning to solve different kinds of problems with different learners is less clear. This paper identifies the different components of a PBLE, including a problem to solve, worked examples, case studies, analogues, prior experiences, alternative perspectives, and simulations. Additionally, different cognitive scaffolds necessary to help students interpret and use those components include analogical encoding, causal relationships, argumentations, questioning, modeling, and metacognitive regulation. Recommendations are provided for matching components and scaffolds with learners’ needs when solving different kinds of problems.

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Ahn, W., Kalish, C. W., Medin, D. L., & Gelman, S. (1995). The role of covariation versus mechanism information in causal attribution. Cognition, 54, 299-352.

Armarego, J. (2002). Advanced software design: A case in problem-based learning. IEEE Computer Society: Proceedings of the 15th Annual Conference on Software Engineering Education and Training.

Atkinson, R., Derry, S. J., Renkl, A. & Wortham, D. (2001). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70, 181- 215.

Barab, S. A., & Duffy, T. M. (2000). From practice fields to communities of practice. In D. H. Jonassen & S. M. Land (Eds.), Theoretical foundations of learning environments (pp. 25-55). Mahwah, NJ: Lawrence Erlbaum Associates.

Barab, S. A., Squire, K. D., & Dueber, W. (2000). A co-evolutionary model for supporting the emergence of authenticity. Educational Technology Research & Development, 48(2), 37-62.

Catrambone, R; Holyoak, K.J. (1989). Overcoming contextual limitations on problem-solving transfer. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(6), 1147-1156.

Cho, K.L., & Jonassen, D.H. (2003). The effects of argumentation scaffolds on argumentation and problem solving. Educational Technology Research & Development, 50(3), 5-22.

Cline, M.J., & Powers, G. J. (1997). Problem based learning in a chemical engineering undergraduate laboratory. IEEE Frontiers in Education, 350-354.

DeJong, T., & van Joolingen, W.R. (1998). Scientific discovery learning with computers simulations of conceptual domains. Review of Educational Research, 68(2), 179-201.

Dunlap, J. C. (2005). Problem-based learning and self-efficacy: How a capstone course prepares students for a profession. Educational Technology Research and Development, 53(1), 65-85.

Gagne, R.M. (1985). The conditions of learning and theory of instruction. Fort Worth, TX: Holt, Rinehart, & Winston.

Ge, X., & S.M. Land. 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.

Gentner, D. (1983). Structure mapping: A theoretical framework for analogy. Cognitive Science, 77, 155-170.

Gentner, D., & Markman, A.B. (1997). Structure mapping in analogy and similarity. American Psychologist, 52(1), 45-56.

Henry, H., Jonassen, D.H., Winholtz, R.A., & Khana, S.K. (2010, November). Introducing problem-based learning in a materials science course in the undergraduate engineering curriculum. Proceedings of the ASME International Conference IMECE2010, Vancouver, Canada of Cognitive Science, 6, 1-20.

Hestenes, D. (1996). Modeling methodology for physics teachers. Proceedings of the International Conference on Undergraduate Physics Education, College Park, MD.

Hung, W., Jonassen, D.H., & Liu, R. (2008). Problem-based learning. In J.M. Spector, J. G. van Merrienboer, M.D., Merrill, & M. Driscoll (Eds.), Handbook of research on educational communications and technology, 3rd Ed. (pp. 485-506). New York: Lawrence Erlbaum Associates.

Jacobson, M. J., Maouri, C., Mishra, P., & Kolar, C. (1995). Learning with hypertext learning environments: theory, design, and research. Journal of Educational Multimedia and Hypermedia, 4, 321-364.

Jonassen, D.H. (2000). Toward a design theory of problem solving. Educational Technology: Research & Development, 48 (4), 63-85.

Jonassen, D.H. (2006). Modeling with technology: Mindtools for conceptual change. Upper Saddle River, NJ: Prentice-Hall.

Jonassen, D.H. (2007). What makes scientific problems difficult? In D.H. Jonassen (Ed.), Learning to solve complex, scientific problems (pp. 3-23). Mahwah, NJ: Lawrence Erlbaum Associates.

Jonassen, D.H. (2011a). Learning to solve problems: A handbook for designing problem-solving learning environments. New York: Routledge.

Jonassen, D.H. (2011b). Ask systems: Interrogative access to multiple ways of thinking. Educational Technology: Research and Development, 59, 159-175.

Jonassen, D. H. (under review). Designing for decision making. Educational Technology Research and Development.

Jonassen, D.H. & Hernandez-Serrano, J. (2002). Case-based reasoning and instructional design: Using stories to support problem solving. Educational Technology: Research and Development, 50(2), 65-77.

Jonassen, D.H., & Hung, W. (2006). Learning to troubleshoot: A new theory-based design architecture. Educational Psychology Review, 18, 77-114.

Jonassen, D.H., & Hung, W. (2008,). All problems are not equal: Implications for PBL. Interdisciplinary Journal of Problem-Based Learning, 2(2), 6-28.

Jonassen, D.H. & Ionas, I.G. (2008). Designing effective supports for causal reasoning. Educational Technology Research & Development, 56, 287-308.

Klein, G. (1998). Sources of power. Cambridge, MA: MIT Press.

Kolodner, J. (1993). Case-based reasoning. New York: Morgan Kaufman.

LaPlaca, M C. Newstetter, W C. Yoganathan, A P. (2001). Problem-based learning in biomedical engineering curricula. Proceedings - Frontiers in Education Conference. 2, F3E/16-F3E/21 (IEEE cat n 01CH37193).

Mitchell G.G., & Delaney, J. D. (2004). An assessment strategy to determine learning outcomes in a software engineering Problem-based learning course. International Journal of Engineering Education, 20, 494- 502

Nussbaum, E.M., & Sinatra, G.M. (2003). Argument and conceptual engagement. Contemporary Educational Psychology, 28, 384-395.

Ploetzner, R., & Spada, H. (1998). Constructing quantitative problem representations on the basis of qualitative reasoning. Interactive Learning Environments, 5, 95-107.

Savin-Baden, M., & Wilkie, K. (2006). Problem-based learning online. Milton-Keynes, UK: Open University Press.

Schank, R. C. (1990). Tell me a story: Narrative and intelligence. Evanston, IL: Northwestern University Press.

Schank, R. & Abelson, R. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Hillsdale, NJ: Lawrence Erlbaum Associates.

Sherrill, J. M. (1983). Solving textbook mathematical word problems. Alberta Journal of Educational Research 29(2), 140–152.

Shön, D. A. (1993). The reflective practitioner: How professionals think in action. New York: Basic Books.

Spiro, R., Coulson, R., Feltovitch, P., & Anderson, D. (1988). Cognitive flexibility theory: Advanced knowledge acquisition in ill-structured domains. Paper presented at the Tenth Annual Conference of the Cognitive Science Society, Hillsdale, NJ.

Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2, 59-89.

Tan, O. S., & Hung, D. (2007). Problem-based learning in e-learning breakthroughs. Singapore: Thomson Learning.

Van Kampen, P., Nanahan, C., Kelly, M., McLoughlin, E., & O’Leary, E. (2004). Teaching a single physics module through problem based learning in a lecture-based curriculum. American Journal of Physics, 72(6), 829-834.

Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7(1), 1-39.