생물 분류 과정의 두뇌 활성 비교를 통한 과학고 학생과 일반고 학생의 인지적 사고 과정의 차이 규명 = Cognitive Difference of Thinking Process between Science and General High School Students' Brain Activations on Biological Classification

다국어 초록 (Multilingual Abstract)

Biological classification is a convergent and creative thinking process as a representative of inductive reasoning. Also, it is involved in the discovery process of a similarity of object properties, criteria of object classification, and categories of observed objects. In science education context, neurological investigation on biological classification is important to understand the inner process of student's cognitive thinking. Therefore, the purpose of this study was to identify neurological characteristics on biological classification in scientifically gifted students comparing with general student. To identify students' neurological characteristics, 9 gifted students and 9 general high school students were recruited in this study. Block experimental- design was used to measure subjects' BOLD signals of their brain. SPM8 software was applied to analyze the acquired MR image data from the 3.0T fMRI system. We could find functional activation regions of brain during biological classification by the main effect analysis, and identify unique activation regions of the gifted student by group effect analysis. According to the result of this study, there was some significant differences between the gifted students' brain regions and general students' brain activation regions. Also, the gifted student could perform bottom-up type thinking with the related multiple brain systems during classification task. However, the general student could maintain top-down type thinking with the restricted interaction among brain systems. Consequently, thinking process of the science-gifted students during biological classification was related to multiple brain systems with dorsal lateral prefrontal cortex, parietal cortex, visual cortex and basal ganglia. In contrary, the general student's brain system during classification was restricted to partial system with premotor cortex, parietal cortex, visual cortex.

참고문헌 (Reference)

1 이소영, "초등학생의 학년별 생물분류 개념형성에 대한 연구" 한국생물교육학회 32 (32): 16-26, 2004

2 박경화, "제 7차 교육과정에 의한 고등학교 생물Ⅱ 교과서의 동물분류단원에 대한 분석" 한국생물교육학회 31 (31): 157-169, 2003

3 조은미, "생물 계통수 생성의 사고 과정 모형 개발" 한국생물교육학회 33 (33): 13-22, 2005

4 권용주, "대학생들의 귀납적 탐구에서 나타난 과학적 사고의 유형과 과정" 한국과학교육학회 23 (23): 286-298, 2003

5 Jin, G., "fMRI study in posterior cingulate and adjacent precuneus cortex in healthy elderly adults using problem solving task" 318 : 135-139, 2012

6 Inagaki, K., "Young children’s conception of the biological world" 15 : 177-181, 2006

7 Corbetta.M., "Voluntary orienting is dissociated from target detection in human posterior parietal cortex" 3 : 292-297, 2000

8 Mayr. E., "This is Biology : The Science of the Living World" Massachusetts: The belknap press of Harvard University press 2000

9 Seger, C. A., "The roles of the caudate nucleus in human classification learning" 25 : 2941-2951, 2005

10 Maddock, R. J., "The retrosplenial cortex and emotion : new insights from functional neuroimaging of the human brain" 22 (22): 310-316, 1999

11 Small, D. M., "The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention" 18 : 633-641, 2003

12 Hopfinger, J. B., "The neural mechanisms of top-down attentional control" 3 : 284-291, 2000

13 Honey. J. N., "The importance of taxonomy in biological education at advanced level" 20 (20): 103-111, 1986

14 Hatano, G., "The development of biological knowledge : a multi-national study" 8 : 47-62, 1993

15 Kéri, S., "The cognitive neuroscience of category learning" 43 : 85-109, 2003

16 Inhelder, B, "The Early Growth of Longic in the Child : Classification and Seriation" Routledge 1964

17 Sass, K., "Taxonomic and thematic categories : Neural correlates of categorization in an auditory-to-visual priming task using fMRI" 1270 : 78-87, 2009

18 Opfer, J. E., "Revisiting preschoolers’living things concept : a microgenetic analysis of conceptual change in basic biology" 49 : 301-332, 2004

19 Babai, R., "Persistence of the intuitive conception of living things in adolescence" 19 : 20-26, 2010

20 Sack, A. T., "Parietal cortex and spatial cognition" 202 : 153-161, 2009

21 Bear, M. F., "Neuroscience : Exploring the Brain" Lippincott Williams & Wilkins 2001

22 Choi, Y. Y., "Multiple bases of human intelligence revealed by cortical thickness and neural activation" 28 (28): 10323-10329, 2008

23 Nielsen, F. A., "Mining the posterior cingulate : Segregation between memory and pain components" 27 : 520-532, 2005

24 Yamauchi, T., "Learning categories composed of varying instances : The effect of classification, inference and structural alignment" 28 (28): 64-78, 2000

25 National Research Councel, "Inquiry and The National Science Education Standards: A Guide for Teaching and Learning" National Academy Press 2000

26 Klauer, K. J., "Inducing inductive reasoning: Does it transfer to fluid intelligence?" 27 : 1-25, 2002

27 Cropley, A. J., "In praise of convergent thinking" 18 : 391-404, 2006

28 Caveza, R., "Imaging cognition Ⅱ : An empirical review of 275 PET and fMRI studies" 12 (12): 1-47, 2000

29 Ashby, F. G., "Human category learning" 56 : 149-178, 2005

30 Magulis, L., "How many kingdom? Current views of biological classification" 43 : 482-489, 1981

31 Sternberg, R., "Handbook of Intelligence" Cambridge University Press 2000

32 Razoumnikova, O. M., "Functional organization of different brain areas during convergent and divergent thinking : an EEG investigation" 10 : 11-18, 2000

33 Huettel, S. A., "Functional Magnetic Resonance Imaging" Sinauer Associates, Inc 2004

34 Schmithorst, V. J, "Functional MRI evidence for disparate developmental processes underlying intelligence in boys and girls" 31 : 1366-1379, 2006

35 Boettiger, C. A., "Frontal networks for learning and executing arbitrary stimulusresponse associations" 25 : 2723-2732, 2005

36 Blair, M. R., "Extremely selective attention: eye-tracking studies of the dynamic allocation of attention to stimulus features in categorization" 35 : 1196-1206, 2009

37 변정호, "Explicit Categorization Ability Predictor for Biology Classification using fMRI" 한국과학교육학회 32 (32): 524-531, 2012

38 Haxby, J. V., "Dissociation of object and spatial visual processing pathways in human extrastriate cortex" 88 : 1621-1625, 1991

39 Reber, P. J., "Dissociating explicit and implicit category knowledge with fMRI" 15 : 574-583, 2003

40 Dias, R., "Dissociable forms of inhibitory control within prefrontal cortex with an analog of the Wisconsin card sort test : restriction to novel situations and independence from"on-line"processing" 17 : 9285-9297, 1997

41 Goel, V., "Differential involvement of left prefrontal cortex in inductive and deductive reasoning" 93 : b109-b121, 2004

42 Hammer, R., "Differential category learning process : The neural basis of comparison-based learning and induction" 52 : 699-709, 2010

43 Kwon, Y. J., "Development of the classification ability quotient equation through the analysis of science teachers` classification knowledge generated in the pollen classification task" 55 (55): 21-43, 2007

44 Guilford, J. P., "Creativity" 5 : 444-454, 1959

45 Corbetta, M., "Control of goaldirected and stimulus-dirven attention in the brain" 3 : 201-215, 2002

46 Owen, A. M., "Contrasting mechanisms of impaired attentional setshifting in patients with frontal lobe damage or Parkinson’s disease" 116 : 1159-1175, 1993

47 Aizenstein, H. J., "Complementary category learning systems identified using eventrelated functional MRI" 12 : 977-987, 2000

48 Talairach, J., "Co-Planner Stereotaxic Atlas of the Human Brain" Thieme Medical publisher, Inc 1988

49 Waxman, S. R., "Challenging the notion of a theematic preference in young children" 33 : 555-567, 1997

50 Grossman, M., "Category-specific effects in semantic memory : Category-task interactions suggested by fMRI" 30 : 1003-1009, 2006

51 Seger, C. A., "Category learning in the brain" 33 : 203-219, 2010

52 Jiang, X., "Categorization training results in shape and category-selective human neural plasticity" 53 : 891-903, 2007

53 Sachs, O., "Categorical and thematic knowledge representation in the brain : Neural correlates of taxonomic and thematic conceptual relations" 46 : 409-418, 2008

54 Ansari, D., "Bridge over troubled waters : education and cognitive neuroscience" 10 (10): 146-151, 2006

55 Song, M., "Brain spontaneous functional connectivity and intelligence" 41 : 1168-1176, 2008

56 Rosenzweig, M. R., "Biological Psychology: an Introduction to Behavioral and Cognitive Neuroscience" Sinauer Associates, Inc. Massachusetts 2005

57 Nosofsky, R. M., "Attention, similarity, and the identification-categorization relationship" 115 : 39-57, 1986

58 Korsnes, M. S., "An fMRI analysis of object priming and workload in the precuneus complex" 46 : 1454-1462, 2008

59 Kruschke, J. K., "ALCOVE : An exemplar-based connectionist model of category learning" 99 : 22-44, 1992

60 Ashby F. G., "A neuropsychological theory of multiple systems in category learning" 105 (105): 442-481, 1998

61 Becker, S., "A model of hippocampal neurogenesis in memory and mood disorders" 11 : 70-76, 2007