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Tuesday, 23 August 2016

Designers Should Enhance Students’ Ill-Structured Problem-Solving Skills

 Identifying Questions to Investigate
Designers Should Enhance Students’ Ill-Structured Problem-Solving Skills
Namsoo Shin & Steven McGee
Copyright © 2003.

What are ill-structured problems?
Ill-structured problems are ones students face routinely in everyday life. They include important social, political, economic, and scientific problems (Simon, 1973). In order to resemble situations in the real world, ill-structured problems have unclear goals and incomplete information (Voss, 1988).
Students who develop robust solutions for ill-structured problems usually engage in the following processes: a) define the problem, b) generate possible solutions, c) evaluate the alternative solutions by constructing arguments and articulating personal beliefs, d) implement the most viable solution, and e) monitor the implementation (Jonassen, 1997; Shin, Jonassen, & McGee, 2003; Sinnott, 1989).
Why is ill-structured problem solving important?
  • Enhance cognitive skills.
    Well-developed domain knowledge is a primary factor in solving ill-structured problems (Jonassen, 1997; Roberts, 1991). In solving ill-structured problems, students apply their domain knowledge in a meaningful way instead of storing a chunk of concepts in a memory (White & Frederiksen, 1998).
  • Enhance metacognitive skills.
    Ill-structured problems require solvers to control and regulate the selection and execution of a solution process (Brown, Bransford, Ferrara, & Campione, 1983; Flavell, 1987; Gick, 1986; Jonassen, 1997; Jacobs & Paris, 1987). In the ill-structured problem-solving processes, students employ their metacognitive skills, such as change strategies, then modify plans and reevaluate goals in order to reach a optimal solution (White & Frederiksen, 1998).
  • Enhance argumentation skills.
    Since ill-structured problems require students to consider alternative solutions, successful students providing evidence for their solution (Voss, 1988; Voss & Post, 1988; Jonassen, 1997). Therefore, students gain practice justifying their solution in a logical way to persuade others.
How does a designer create ill-structured problems?
  • Design a complicated problem that we face in everyday life.
    Ill-structured problems should come from a real-life situation in which there is no obvious right answer. Problems should be authentic and relevant to students (Howard, McGee, Shin, & Shia, 2001). Ill-structured problems should include vaguely defined goals. The information available to the decision maker should be incomplete or ambiguous (Wood, 1993). Problems should make it unclear which concepts, rules, and principles are necessary for the solution.
  • Design a problem including multiple solutions and perspectives. 
    Ill-structured problems must allow alternative solutions instead of one correct answer (Meacham & Emont, 1989). Additionally, ill-structured problems should allow students to pursue different procedures for solving the problem. These various procedures will come from allowing different perspectives based on students’ perceptions and interpretations of the nature of the problem. 
Brown, A. L., Bransford, J., Ferrara, R., & Campione, J. (1983). Learning, remembering, and understanding. In P.H. Musen (Ed.), Handbook of child psychology: Vol. III (pp. 77-166). New York: Wiley.

Flavell, J. H. (1987). Speculations about the nature and development of metacognition. In F. Weinert & U.R. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 21-29). Hillsdale, NJ: Erlbaum.

Gick, M. L. (1986). Problem-solving strategies. Educational Psychologist, 21, 99-120.

Howard, B., McGee, S., Shin, N, & Shia, R (2001). The triarchic theory of intelligence and computer-based inquiry learning. Educational Technology Research and Development, 49(4), 49-69.

Jacobs, J. E., & Paris, S. G. (1987). Children’s metacognition about reading: Issues in definition, measurement, and instruction. Educational Psychologist, 22, 255-278.

Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology: Research and Development, 45(1), 65-94.

Meacham, J. A., & Emont, N. M. (1989). The interpersonal basis of everyday problem solving. In J. D. Sinnott (Ed.), Everyday problem solving: Theory and applications (pp. 7-23). New York: Praeger.
Roberts, D. A. (1991). What counts as an explanation for a science teaching event? Teaching Education, 3, 69-87.

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

Simon, H. A. (1973). The structured of ill-structured problem. Artificial Intelligence, 4, 1981-201.

Sinnott, J. D. (1989). A model for solution of ill-structured problems: Implications for everyday and abstract problem solving. In J. D. Sinnott (Ed.), Everyday problem solving: Theory and applications (pp. 72-99). New York: Praeger.

Voss, J. F. (1988). Problem solving and reasoning in ill-structured domains. In C. Antaki (Ed.), Analyzing everyday explanation: A casebook of methods (pp. 74-93). London: SAGE Publications.
Voss, J. F., & Post, T. A. (1988). On the solving of ill-structured problems. In M. T. H. Chi, R. Glaser, & M. J. Farr (Eds.) The nature of expertise. Hillsdale, NJ: Lawrence Erlbaum.

White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16(1), 3-18.

Wood, P. K. (1993). Inquiring systems and problem structures: Implications for cognitive developments. Human Developments, 26, 249-265.

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