바로가기메뉴

본문 바로가기 주메뉴 바로가기

logo

The Effects of cognitive styles, stimulus cohesiveness, and instructions on category learning

The Korean Journal of Cognitive and Biological Psychology / The Korean Journal of Cognitive and Biological Psychology, (P)1226-9654; (E)2733-466X
2011, v.23 no.3, pp.411-429
https://doi.org/10.22172/cogbio.2011.23.3.007

  • Downloaded
  • Viewed

Abstract

This study investigated whether the differences of wholistic processors and analytic processors in information processing strategies had an effect on categorization performances and whether these differences could be overcame by rule instruction. In Experiment 1, the effects of perceptual cohesiveness in categorization performances of wholistic processors and analytic processors were analyzed in detail. Results showed that perceptual cohesiveness didn't make any influence in category judgements of analytic processors. However, wholistic processors categorized highly cohesive exemplars more quickly and accurately than low cohesive exemplars in positive transfer condition, but no differences in negative transfer condition. Experiment 2 inquired whether categorization performances of wholistic processors could be improved by rule instruction in low cohesive condition. It was found that rule instruction improved categorization performances in low cohesive condition, and wholistic processors could categorize exemplars by rule extraction. But, Wholistic processors categorized highly cohesive exemplars inaccurately and slowly in negative transfer condition, which implied that wholistic processors were strongly influenced by similarity conditions in spite of rule instruction. In conclusion, analytic processors tend to learn categories by rule extraction and wholistic processors by memorizing exemplars and comparing similarities between them, bu`t the difference could be diminished by learning strategies such as rule instruction.

keywords
인지양식, 자극 응집성, 지시, 전체처리자, 분석처리자, cognitive style, perceptual cohesiveness, instruction, wholistic processor, analytic processor

Reference

1.

고지룡 (2006). 인지양식에 따른 개념도 점검 방법이 개념도 형성 및 설명적 글쓰기에 미치는 효과. 전남대학교 교육대학원, 석사학위논문.

2.

김미라, 유현주, 이정모, 박태진 (2003). 인지양식이 글 이해와 요약에 미치는 효과. 한국인지과학회 춘계학술대회 발표논문집, 137- 140.

3.

박정민, 김신우, 이지선, 손영우, 한광희 (2003). 시간압력 상황에서 인지양식과 학습맥락이 시각변별의 기술습득과 전이에 미치는 효과. 감성과학, 6(3), 63-73.

4.

이관용․이태연 (1996). 자극유형이 범주화 방략의 선택에 미치는 영향: 언어자극과 그림자극을 중심으로. 한국심리학회지: 실험 및 인지, 8, 303-316.

5.

이태연 (2009). 범주학습에서 범주화 방략에 미치는 인지양식의 효과. 한국심리학회지: 인지 및 생물, 20, 339-355.

6.

조경자·한광희 (2002). 멀티미디어 환경에서 인지양식이 학습수행에 미치는 영향. 한국심리학회지: 실험 및 인지, 14(3), 165-185.

7.

정광희, 이정모 (2005). 지식유형과 인지양식이 글 요약과 이해에 미치는 영향. 인지과학, 16(4), 271-285.

8.

조증렬 (1994). 자극유형과 범주구조가 범주화와 재인에 미치는 영향. 한국심리학회지: 실험 및 인지, 6, 77-93.

9.

Allen, S. W., & Brooks, L. (1991). Specializing the operation of an explicit rule. Journal of Experimental Psychology: General, 120, 3-19.

10.

Berry, D. C., & Broadbent, D. E. (1988). Interactive tasks and the implicit-explicit distinction. British Journal of Psychology, 79, 251-272.

11.

Bruner, J., Goodnow, J., & Austin, A. (1956). A Study of Thinking. New York: Wiley.

12.

Danks, J. H., & Gans, D. L. (1975). Acquisition and utilization of a rule structure. Journal of Experimental Psychology: Human learning and memory, 1, 201-208.

13.

Davies, J., & Graff, M. (2006). Wholist-analytic cognitive style: A matter of reflection. Personality and Individual Differences, 41, 989 -997.

14.

Estes, W. K. (1986). Memory storage and retrieval processes in category learning. Journal of Experimental Psychology: General, 115, 155-174.

15.

Foard, C. F., & Kemler-Nelson, D. G. (1984). Holistic and analytic modes of processing: The multiple determinants of perceptual analysis. Journal of Experimental Psychology: General, 113, 94-111.

16.

Howard, J. H., & Ballas, J. A. (1980). Syntactic and semantic factors in the classification of nonspeech transient patterns. Perception and Psychophysics, 28, 431-439.

17.

Hudson, L. (1966). Contrary imaginations. Harmondsworth: Penguin.

18.

Kagan, J. (1965). Indivisual differences in the resolution of response uncertainty. Journal of Personality and Social Psychology, 2, 154-160.

19.

Kulik, J. A., Kulik, C. C., & Shwalb, B. J. (1986). The effectiveness of computer-based adult education: A meta-analysis. Jounral of Educational Computing Research, 2, 235-252.

20.

Levine, M. (1966). Hypothesis behavior by humans during discrimination learning. Journal of Experimental Psychology, 71, 331-338.

21.

McAndrews, M. P., & Moscovitch, M. (1985). Rule-based and exemplar-based classification in artificial grammar learning. Memory & Cognition, 13, 469-475.

22.

Martin, R. C., & Caramazza, A. (1980). Classification in well-defined and ill-defined categories: Evidence for common processing strategies. Journal of Experimental Psychology: General, 109, 320-353.

23.

Medin, D. L., & Schaffer, M.M. (1978). Context theory of classification learning. Psychological Review, 85, 207-238.

24.

Modigliani, V., & Rizza, J. P. (1971). Conservation of simple concepts as a function of deletion of irrelevant attributes. Journal of Experimental Psychology, 90, 280-286.

25.

Najjar, L. J. (1996). Multimedia information and learning. Journal of Educational Multimedia and Hypermedia, 5, 129-150.

26.

Nosofsky, R. M., Clark, S. E., & Shin, H. J. (1989). Rules and exemplars in categorization, identification, and recognition. Journal of Experimental Psychology: Learning, memory, and cognition, 15, 282-304.

27.

Peterson, E. R., Deary, I. J., & Austin, E. J. (2003). A new measure of verbal-imagery cognitive style: VICS. Personality and Individual Differences, 38, 1269-1281.

28.

Rayner, S., & Riding, R. (1997). Towards a categorization of cognitive styles and learning styles. Educational Psychology, 17, 5-28.

29.

Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118, 219-235.

30.

Regehr, G., & Brooks, L. R. (1993). Perceptual manifestations of an analytic structure: The priority of holistic individuation. Journal of Experimental Psychology: General, 122, 92-114.

31.

Rezaei, A. R., & Katz, L. (2004). Evaluation of the reliability and validity of the cognitive styles analysis. Personality and Individual Differences, 26, 1317-1327.

32.

Riding, R. J., & Cheema, I. (1991). Cognitive styles-an overview and integration. Educational Pscyhology, 11, 193-215.

33.

Riding, R., & Rayner, S. (1998). Cognitive styles and learning strategies: understanding style differences in learning and behavior. London: Foulton.

34.

Riding, R. J., & Sadler-Smith, E. (1997). Cognitive style: some implications for training design. Internaltional Journal of Training and Development, 1(3), 199-340.

35.

Riding, R., & Rayner, S. (2001). Cognitive Styles and Learning Strategies. London: David Fulton Publishers.

36.

Robey, D. & Taggard, W. (1981). Measuring manager's minds: the assessment of style in human information processing. Academy of Management Review, 6, 375-383.

37.

Smith, E. E., & Medin, D. (1981). Categories and Concepts. Cambridge, MA: Harvard University Press.

38.

Strehler, A. (2008). The relationship between cognitive load, cognitive style and multimedia learning. Unpublished doctoral dissertation, University of Pretoria.

39.

Sweller, J. (1989). Cognitive technology: Some procedures for facilitating learning and problem solving in mathematics and science. Journal of Educational Psychology, 81 (4), 457-466.

40.

Ward, T. B., & Becker, A. H. (1992). Learning categories with and without trying: Does it make a difference? In B. Burns (Ed.), Percepts, concepts, and categories (451-491). N.Y.: North-Holland Press.

41.

Witkin, H. A. (1962). Psychological differentiation: studies of developtment. New York: Wiley.

The Korean Journal of Cognitive and Biological Psychology