Predicting problem-solving performance using concept map

A growing community of researchers applies the concept map for elicitation and representation individual's knowledge structure especially within knowledge-intensive processes in organizations. As an extension of prior works on concept map, this study aims to explore a new indicator of structural properties of concept map from an information entropy perspective to predict an individual's problem-solving performance. From the information processing view of problem-solving, Information Theory provides the framework to formulate a new indicator called EntropyAvg. A controlled experiment was carried out to validate the predictive ability of the new indicator. The results demonstrate that EntropyAvg is able to estimate an individual's problem-solving performance beyond two other widely adopted indicators, i.e., complexity and integration. The theoretical and practical contributions of this study are also discussed.