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

Background

Strategies to support problem solving are common but there are not any instructional design models to support the process of learning how to solve problems. Jonassen (1997) proposes models for the problem solving process and models for designing problem-solving instruction. To do this, he defines problems as consisting of a problem domain, problem type, problem-solving process, and a solution. The three types of problems on a continuum from decontextualized problems with convergent solutions to very contextualized problems with multiple solutions are puzzle problems, well-structured problems, and ill-structured problems. He focuses on well-structured and ill-structured problems by first proposing the problem-solving process and the supporting instructional design for well-structured problems and then proposing the problem-solving process and the supporting instructional design for ill-structured problems. These recommendations can be used by designers to implement problem-solving instruction.

A Summary of Key Points

  • Information processing theory is the basis for instructional design of well-structured problems.
  • The problem-solving process for well-structured problems is outlined in three steps. Figure 1: Schematic of problem-solving process as developed by Gick (Jonassen, 1997, p. 70) illustrates one model used to develop this process. The first step is to understand the task. The second step is to generate possible solutions. The third step is to try out the solutions.
  • Constructivism and situated cognition form the basis for instructional design for ill-structured problems.
  • The problem-solving process for ill-structured problems is outlined in seven steps. The first step is for the learner to identify the problem space and any contextual constraints. The second step is for the learner to identify and clarify alternative views or perspectives of stakeholders. The third step is to focus on solutions for the problems. The fourth step is to develop arguments in support of their solution and develop a personal position statement about their solution. The fifth step is to monitor the problem space and solution options. The sixth step is implement the solution and monitor how it performs. The final step is to adapt the solution as needed.
  • Design PrinciplesDeveloping and designing well-structured problem-solving instruction is outlined as follows:
    • Step 1: Review prerequisite component concepts, rules, and principles
    • Step 2: Present conceptual or casual model of problem domain
    • Step 3: Model problem solving performance in worked examples
    • Step 4: Present practice problems
    • Step 5: Support the search solutions
    • Step 6: Reflect on problem state and problem solution

    Developing and designing Ill-structured problem-solving instruction, as represented in Table 1: Implementation process for ill-structured problems (Jonassen, 1997, p. 87), is outlined as follows:

    • Step 1: Articulate problem context
    • Step 2: Introduce problem constraints
    • Step 3: Locate, select, and develop cases for learners
    • Step 4: Support knowledge base construction
    • Step 5: Support argument construction
    • Step 6: Assess problem solutions

Example Work

  1. Using well-structured problem solving to solve a genetics practice problem
    • A step-by-step example of a well-structured problem solution (91).
  2. Using ill-structured problem solving to solve a performance problem
    • A step-by-step example of an ill-structured problem solution (94).

Discussion Questions

  1. Why are both well-structured and ill-structured problem solving learning outcomes important?
  2. As a designer, how would you create an ill-structured problem?
  3. Jonassen (1997) concludes the article by saying that the models presented are not definitive answers but works in progress. What additional experimentation or assessment of the models could be done to move towards a definitive model?

Additional Resources

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