Abstract

This study investigated the kinds of knowledge necessary to learn an important troubleshooting strategy, elimination. A total of 50 college-level students searched for the source of failures in simple digital networks. Production system modelling suggested that students using a common but simpler backtracking strategy would learn the more advanced elimination strategy if they applied certain domain-specific knowledge and the general-purpose problem-solving strategy of reductio ad absurdum. In an experiment, students solved network troubleshooting problems after being trained with either the domain-specific knowledge, the reductio ad absurdum strategy, both types of knowledge, or neither. Students needed both the domain-specific and general knowledge identified by the models in order to significantly increase their elimination use.