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Jonassen, D. H., (2000). Toward a design theory of problem solving. Education Technology Research and Development, 48(4), 63-65.
Background
Problem solving is a common, everyday activity in both personal and professional contexts. However, there is little research in instructional design literature to support specific models of problem-solving instruction and the process of learning to solve problems. In earlier research, Jonassen (2000) began to explore the instructional design requirements by differentiating between well-structured and ill-structured problems. This article builds upon that by defining the attributes of problems and problem solving and suggests a typology of problem-solving outcomes. To determine the problem types, hundreds of problems were collected. A cognitive task analysis was conducted to identify attributes. Finally, an iterative sort distinguished 11 different types of problems.
Summary of Key Points
- Problem solving requires the mental representation of the situation and requires manipulation of the problem space. Problem solving is not a uniform activity.
- One dimension of problem solving is problem variations. Problems are defined as well-structured or ill-structured and require different skills to solve. Problems also vary in their complexity with problem difficulty being of function of problem complexity. Problem-solving skills are dependent upon the nature of the context or domain.
- A second dimension of problem solving is representation. Instructional designers must be aware of context, cues, and modality when representing problems.
- A third dimension of problem solving is individual differences. Individual characteristics of learners may affect problem solving. Some of those traits include familiarity, domain and structural knowledge, cognitive controls, metacognition, epistemological believes, affective and conative elements, and general problem-solving skills.
Design Principles
Jonassen (2000) presents a typology of problem classes that practitioners and learners need to learn to solve as solving different kinds of problems calls on different kinds of knowledge and skills. The problem types are on a continuum of well-structured to ill-structured. The typology is taxonomic with well-structured problems being a prerequisite to ill-structured problems.
The typology, with additional details in Table 1: Problem typology varying from well-defined on the top to ill-defined on the bottom (Jonassen, 2000, p. 74), is as follows:
- Logical Problems: abstract tests of reasoning that puzzle the learner
- Algorithmic Problems: repeating a series of steps through a procedure or formula
- Story Problems: story with formula or procedure embedded
- Rule-Using Problems: clear purpose or goal that is constrained but not restricted to a specific procedure or method
- Decision-Making Problems: selecting a single option from a set of alternatives based on a set of criteria
- Troubleshooting Problems: fault state diagnosis
- Str