Prescribing Effective Human Problem-Solving Processes: Problem Description in Physics

Abstract

We formulate a theoretical model specifying the underlying knowledge and procedures whereby human problem solvers can generate useful initial descriptions of scientific problems. This model is prescriptive, that is, it does not necessarily try to simulate the behavior of actual experts nor assume that their performance is optimal. To test such a model, formulated for the domain of mechanics, we devised a carefully controlled experiment where human subjects were induced to act in accordance with specified alternative models and where their resulting performance was observed in detail. The results show that the proposed model is sufficient to generate excellent problem descriptions, that these markedly improve subsequent problem solutions, and that major components of the model are necessary for good performance. Furthermore, detailed analysis of the data shows how the model predictably prevents the occurrence of many common errors. Such a validated prescriptive model provides a useful basis for teaching students improved problem-solving skills.