Publication | Open Access
Problem Solving in Semantically Rich Domains: An Example from Engineering Thermodynamics*
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Artificial IntelligenceEngineeringTask AnalysisModel-based ReasoningCognitionSemanticsSemantic WebLanguage ProcessingSocial SciencesProblem Solving EnvironmentComputational LinguisticsKnowledge EngineeringChemical Engineering ThermodynamicsSemantically RichHuman LearningKnowledge RepresentationCognitive ScienceComputer ScienceHuman ProblemProblem-based LearningReasoningHuman Problem SolvingAutomated ReasoningProblem SolvingDomain ModelComputational SemanticsSemantic Representation
Recent research on human problem solving has largely focused on laboratory tasks that do not demand from the subject much prior, task‐related information. This study seeks to extend the theory of human problem solving to semantically richer domains that are characteristic of professional problem solving. We discuss the behavior of a single subject solving problems in chemical engineering thermodynamics. We use as a protocol‐encoding device a computer program called SAPA which also doubles as a theory of the subject's problem‐solving behavior. The subject made extensive use of means‐ends analysis, similar to that observed in semantically less rich domains, supplemented by recognition mechanisms for accessing information in semantic memory.
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