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PROBLEM-DESIGN HEURISTICS

Problems can be designed to support interdisciplinary interaction, by limiting the complexity of problem and reducing the scope of the problem space such that interdisciplinary solutions are easier to locate

These heuristics are most suitable for:

Interactions
Mixed or single groups

Degree of Integration
Multidisciplinary or interdisciplinary

Problem structure
Structured problems

Skill targets
 Interdisciplinary problem-solving

What are Problem-Design Heuristics?

These are a set of design heuristics which can be used to inform the construction of a problem which helps scaffold interdisciplinary interaction for a known set of disciplines. These operate principally to reduce the complexity of the problem space for students and remove obstacles to interdisciplinary engagement through the design of the problem itself.

Heuristics

  • Goal Structuring

    One aspect of a problem or project task which can be structured is the outcome required, and this can be explicitly framed in ways which narrow problem-spaces for students either in the description of the problem and its targets, or assessment criteria.

  • Process Structuring

    The problem or project task can be constrained through instructions or suggestions of specific methods to employ, which might include setting the specific variables to be studied or by giving data of a particular kind. These limitations can guide students towards an optimal result. Some of these can be introduced in project-task context by training students in specific methods for interdisciplinary projects before engaging in the project, on the basis that the project is an opportunity to apply those methods.

  • Problem Balance

    Problem-balance in respect of interdisciplinary problem-solving is the degree to which the problems are balanced with respect to the various disciplines participating. Balance can have a few meanings in this sense. It can refer to whether the problem is an equally meaningful problem for each group. A problem essentially focused on health care might have little relevance to ecologists for instance. We could call this “balance in opportunity”, which could be measured by the degree to which a problem is close to existing subjects of interests and methods of each of the involved disciplines. But for problems that are more closed, balance can also refer to the degree to which the time, energy, degree of intellectual contribution prescribed in the problem description are balanced for each discipline. We can call this “balance in contribution”. This latter could also be measured in terms of how central certain disciplines may be to the problem and whether certain disciplines are given a leading role by the problem design, while others are relegated to support roles, when it comes to optimal solutions. Principally either kind of balance can be managed through careful problem design, and balance should be thought of as a specific design parameter.

  • Problem Modularity

    Modularizing a problem can help ensure that the problem is relatively decomposable into separate problems which are optimally resolved using methods from specific disciplines. This should not be taken to imply that the problem should simply be constructed as separate discrete problems with no interconnections. But the required interconnections should not be so complex or uncertain so as to prevent disciplines solving their parts effectively. It may of course leave open to the students how to resolve and manage or integrate the parts, and this could require some deeper interdisciplinary thinking from students. Modularizing problems can serve to dramatically cut down interdisciplinary problem complexity and shift emphasis onto problem solving and integration.