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Tools for Representing Problems and the Knowledge Required to Solve Them

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Book cover Knowledge and Information Visualization

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3426))

Abstract

In this chapter, I have shown that problem solving depend on how the problem is represented to the learners. That representation affects, to some degree, they ways that problem solvers represent problem mentally. A more efficacious way of affecting those internal mental representation is to provide students with a variety of knowledge representation tools, such as concept maps, expert systems, and systems dynamics tools, to represent the problem space, that is, their mental representation of the problem and the domain knowledge required to solve it.

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References

  • Adams-Webber, J.: Constructivist psychology and knowledge elicitation. Journal of Constructivist Psychology 8(3), 237–249 (1995)

    Article  Google Scholar 

  • Anderson, J.R.: The architecture of cognition. Harvard University Press, Cambridge (1983)

    Google Scholar 

  • Carroll, J.M., Thomas, J.C., Malhotra, A.: Presentation and representation in design problem solving. British Journal of Psychology 71, 143–153 (1980)

    Google Scholar 

  • Chi, M.T.H., Bassock, M.: Learning from examples vs. self-explanations. In: Resnick, L.B. (ed.) Knowing, learning, and instruction: Essays in honor of Robert Glaser, pp. 251–282. Lawrence Erlbaum Associates, Hillsdale (1991)

    Google Scholar 

  • Chi, M.T.H., Feltovich, P.J., Glaser, R.: Categorization and representation of physics problems by experts and novices. Cognitive Science 5, 121–152 (1981)

    Article  Google Scholar 

  • Chipman, S.F., Segal, J.W., Glaser, R.: Thinking and learning skills, vol. 2. Erlbaum, Hillsdale (1985)

    Google Scholar 

  • Cho, K.L., Jonassen, D.H.: The effects of argumentation scaffolds on argumentation and problem solving. Educational Technology: Research & Development 50(3), 5–22 (2002)

    Article  Google Scholar 

  • de Jong, T., Ferguson-Hessler, M.G.M.: Knowledge of problem situations in physics: a comparison of good and poor novice problem solvers. Learning and Instruction 1, 289–302 (1991)

    Article  Google Scholar 

  • Dunkle, M.E., Schraw, G., Bendixen, L.D.: Cognitive processes in well-defined and ill-defined problem solving. In: Paper presented at the annual meeting of the American Educational Research Association, San Francisco (1995)

    Google Scholar 

  • Gagne, R.M.: Conditions of learning, 4th edn. Rinehart & Winston, New York (1985)

    Google Scholar 

  • Gick, M.L., Holyoak, K.J.: Analogical problem solving. Cognitive Psychology 12, 306–355 (1980)

    Article  Google Scholar 

  • Gick, M.L., Holyoak, K.J.: Schema induction and analogical transfer. Cognitive Psychology 15, 1–38 (1983)

    Article  Google Scholar 

  • Hegarty, M., Mayer, R.E., Monk, C.A.: Comprehension of arithmetic word problems: A comparison of successful and unsuccessful problem solvers. Journal of Educational Psychology 87, 18–32 (1995)

    Article  Google Scholar 

  • Hong, N.S., Jonassen, D.H., McGee, S.: Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching 40(1), 6–33 (2003)

    Article  Google Scholar 

  • Jonassen, D.H.: Computers as cognitive tools: Mindtools for critical thinking. Merrill/Prentice-Hall, Columbus (1996)

    Google Scholar 

  • Jonassen, D.H.: Instructional design model for well-structured and ill-structured problem-solving learning outcomes. Educational Technology: Research and Development 45(1), 65–95 (1997)

    Article  Google Scholar 

  • Jonassen, D.H.: Computers as Mindtools in schools: Engaging critical thinking. Merrill/Prentice-Hall, Columbus (2000)

    Google Scholar 

  • Jonassen, D.H., Henning, P.: Mental models: Knowledge in the head and knowledge in the world. Educational Technology 39(3), 37–42 (1999)

    Google Scholar 

  • Jonassen, D.H., Kwon, H.I.: Communication patterns in computer-mediated vs. face-to-face group problem solving. Educational Technology: Research and Development 49(10), 35–52 (2001)

    Article  Google Scholar 

  • Jonassen, D.H., Beissner, K., Yacci, M.A.: Structural knowledge: Techniques for representing, conveying, and acquiring structural knowledge. Lawrence Erlbaum Associates, Hillsdale (1993)

    Google Scholar 

  • Kleinmutz, D.N., Schkade, D.A.: Information displays and decision processes. Psychological Science 4(40), 221–227 (1993)

    Article  Google Scholar 

  • Larkin, J.H.: The role of problem representation in physics. In: Gentner, D., Stevens, A.L. (eds.) Mental models, pp. 75–98. Lawrence Erlbaum Associates, Hillsdale (1983)

    Google Scholar 

  • Larkin, J.H.: Understanding, problem representation, and skill in physics. In: Chipman, S.F., Segal, J.W., Glaser, R. (eds.) Thinking and learning skills Research and open questions, vol. 2, pp. 141–160. Erlbaum, Hillsdale (1985)

    Google Scholar 

  • Lippert, R.: Teaching problem solving in mathematics and science with expert systems. School Science and Mathematics 87, 407–413 (1987)

    Article  Google Scholar 

  • Mayer, R.E.: Comprehension as affected by structure of problem representation. Memory & Cognition 4(3), 249–255 (1976)

    Article  Google Scholar 

  • McGuinness, C.: Problem representation: The effects of spatial arrays. Memory & Cognition 14(3), 270–280 (1986)

    Article  Google Scholar 

  • Morgan, M.S.: Learning from models. In: Morgan, M.S., Morrison, M. (eds.) Models as mediators: Perspectives on natural and social science, pp. 347–388. Cambridge University Press, Cambridge (1999)

    Chapter  Google Scholar 

  • Nickerson, R.S., Perkins, D.N., Smith, E.E.: The teaching of thinking. Erlbaum, Hillsdale (1985)

    Google Scholar 

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

    Article  Google Scholar 

  • Ploetzner, R., Fehse, E., Kneser, C., Spada, H.: Learning to relate qualitative and quantitative problem representations in a model-based setting for collaborative problem solving. Journal of the Learning Sciences 8(2), 177–214 (1999)

    Article  Google Scholar 

  • Potts, G.R., Scholz, K.W.: The internal representation of a three-term series problem. Journal of Verbal Learning & Verbal Behavior 14(5), 439–452 (1975)

    Article  Google Scholar 

  • Reed, S.K.: A structure mapping model for word problems. Journal of Experimental Psychology: Learning, Memory, and Cognition 13, 124–139 (1987)

    Article  Google Scholar 

  • Reimann, P., Chi, M.T.H.: Human expertise. In: Gilhooly, K.J. (ed.) Human and machine problem solving, pp. 161–191. Plenum, New York (1989)

    Google Scholar 

  • Salomon, G.: AI in reverse: Computer tools that turn cognitive. Journal of Educational Computing Research 4(2), 123–139 (1988)

    Article  Google Scholar 

  • Savelsbergh, E.R., de Jong, T., Ferguson-Hessler, M.G.M.: Competence-related differences in problem representations. In: van Sommeren, M., Reimann, P., de Jong, T., Boshuizen, H. (eds.) The role of multiple representations in learning and problem solving, pp. 262–282. Elsevier, Amsterdam (1998)

    Google Scholar 

  • Schwartz, S.H.: Modes of representation and problem solving: Well evolved is half solved. Journal of Experimental Psychology 91, 347–350 (1971)

    Article  Google Scholar 

  • Schwartz, S.H., Fattaleh, D.L.: Representation in deductive problem solving: The matrix. Journal of Experimental Psychology 95, 343–348 (1973)

    Article  Google Scholar 

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

    Google Scholar 

  • Simon, D.P.: Information processing theory of human problem solving. In: Estes, D. (ed.) Handbook of learning and cognitive process, pp. 271–295. Lawrence Erlbaum Associates, Hillsdale (1978)

    Google Scholar 

  • Simon, H.A.: Studying human intelligence by creating artificial intelligence. American Scientist 69(3), 300–309 (1981)

    Google Scholar 

  • Singly, M.K., Anderson, J.R.: The transfer of cognitive skill. Harvard University Press, Cambridge (1989)

    Google Scholar 

  • Slack, S., Stewart, J.: Improving Student Problem Solving in Genetics. Journal of Biological Education 23(49), 308–312 (1990)

    Google Scholar 

  • Soloway, E., Krajcik, J., Finkel, E.A.: Science project: Supporting science modeling and inquiry via computational media and technology. American Educational Research Association, San Francisco (1995)

    Google Scholar 

  • Starfield, A.M., Smith, K.A., Bleloch, A.L.: How to model it: Problem solving for the computer age. McGraw-Hill, New York (1990)

    Google Scholar 

  • Sweller, J., Chandler, P.: Why some material is difficult to learn. Cognition and Instruction 12, 185–233 (1994)

    Article  Google Scholar 

  • Zhang, J.: The nature of external representation in problem solving. Cognitive Science 21, 179–217 (1997)

    Article  Google Scholar 

  • Zhang, J., Norman, D.: Representations in distributed cognitive tasks. Cognitive Science 18, 87–122 (1994)

    Article  Google Scholar 

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Jonassen, D.H. (2005). Tools for Representing Problems and the Knowledge Required to Solve Them. In: Tergan, SO., Keller, T. (eds) Knowledge and Information Visualization. Lecture Notes in Computer Science, vol 3426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11510154_5

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  • DOI: https://doi.org/10.1007/11510154_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26921-2

  • Online ISBN: 978-3-540-31962-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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