본 연구는 인지양식검사(CSA)를 사용하여 피험자를 전체처리자와 분석처리자로 구분하고, 두 처리자가 범주를 학습할 때 서로 다른 범주화 방략을 사용하는지 검토하였다. 실험 1에서는 선형범주와 비선형범주를 제시하고 두 처리자가 어느 범주를 더 빨리 학습하는지를 비교하였다. 분석처리자는 선형범주를 비선형범주보다 빠르게 학습하였으나, 전체처리자는 선형조건간의 차이가 관찰되지 않았다. 또한 재인과제에서 전체처리자가 분석처리자에 비해 더 높은 정확재인율을 보였다. 실험 2에서는 전이사례와 예외사례에 대한 피험자의 범주판단을 개별적으로 분석하여 두 처리자가 범주를 학습할 때 사용하는 범주화 방략을 살펴보았다. 실험 2의 결과에 따르면 분석처리자는 특정한 속성에 선택적 주의를 기울이는 분석적 방략을 더 많이 사용하지만, 전체처리자는 사례간의 유사성을 비교하는 비분석적 방략을 더 많이 사용하였다. 이러한 결과를 볼 때 분석처리자는 범주를 정의하는 규칙을 찾아 범주를 학습하는데 비해 전체처리자는 학습했던 사례와의 유사성을 비교하여 범주를 학습하는 경향이 있다.
This study investigated whether participants adopted different categorization strategies to learn categories according to their cognitive styles. At first, participants were classified into two types of processor, analytic processors and wholistic processors by Riding(1991)'s cognitive style analysis(CSA). Manipulating linear separability of category structure, learning speed of two processors were compared in Experiment 1. Results showed that analytic processors learned linearly separated categories more quickly than wholistic processors, and wholistic processors reminded learned exemplars more accurately than analytic processors. In Experiment 2, Analyzing categorization patterns of subjects individually, hypothesis was tested that two processors used different categorization strategies to learn categories. Experiment 2's hypothesis was confirmed partially. In conclusion, analytic processors learned categories by focusing attention on relevant features and wholistic processors by comparing similarity between new exemplar and learned exemplars.
This study investigated whether participants adopted different categorization strategies to learn categories according to their cognitive styles. At first, participants were classified into two types of processor, analytic processors and wholistic processors by Riding(1991)'s cognitive style analysis(CSA). Manipulating linear separability of category structure, learning speed of two processors were compared in Experiment 1. Results showed that analytic processors learned linearly separated categories more quickly than wholistic processors, and wholistic processors reminded learned exemplars more accurately than analytic processors. In Experiment 2, Analyzing categorization patterns of subjects individually, hypothesis was tested that two processors used different categorization strategies to learn categories. Experiment 2's hypothesis was confirmed partially. In conclusion, analytic processors learned categories by focusing attention on relevant features and wholistic processors by comparing similarity between new exemplar and learned exemplars.
