Particular surface features of problems can become associatively linked with effective, wellmastered solution principles, thus modifying their application and producing faster solutions. In 3 experiments, 8 3-bit decision rules were used to solve word problems generated from experimentally restricted feature pools. The authors confirmed that frequency of exposure to surface speeds problem encoding and categorization. Co-occurence between particular problem features and a relevant rule (particularization) resulted in outracing of well-learned problem-solving processes by direct linkage between features and action choice. Particularization, an inductive process emerging during rule-guided problem solving, is proposed as a mechanism by which rule-guided decisions become automatized. In this way, memories of specific rule-application experiences supplant analytic processes in problem solving. (A)
Abstract