Journal of The Korean Association For Science Education (한국과학교육학회지)

The Korean Association for Science Education (한국과학교육학회)
권호 표지

EEG Correlation Patterns of Hypothesis-Generating in Undergraduate Students' Generation of Scientific Knowledge

  • Published : 2004.08.30
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study was to test the notion that the inter-individual difference in hypothesis-generating is presumably detected by differentiating subjects' EEG correlation patterns of the prefrontal lobes. To test the notion of the inter-individual difference by EEG analysis, eight healthy undergraduate volunteers' EEG signals on the prefrontal lobes were recorded during hypothesis-generating and resting with eyes-closed condition. Their EEG signals were analyzed by time durations and transformed into correlation patterns. The results showed that subjects' EEG correlation patterns during hypothesis-generating were significantly different among individuals. In addition, the EEG correlation patterns were decreased during hypothesis-generating thinking. Furthermore, subject's EEG correlation showed a fluctuationpattern through-out hypothesis-generating, which is presumably caused by the difference of subjects' thinking activities in hypothesis-generating. This study also suggests a possibility that student's scientific thinking ability and the difficulty of scientific knowledge generating may be measured by the analysis of subject's EEG correlation pattern of the prefrontal lobes.

Keywords

References

  1. Anderson, J. R. (1995). Cognitive psychology and its implications (4th ed.). New York: W. H. Freeman and Company
  2. Baddeley, A. (1986). Working memory. Oxford, Englend: Oxford University Press
  3. Barnhart, C.L. (1953). The American college dictionary. New York: Harper & Brothers
  4. Bear, M. F., Connors, B. W., & Paradiso, M. A. (2000). Neuroscience: Exploring the brain (2nd ed.). Baltimore, MD: Lippincott Williams & Wilkins
  5. Defebvre, L., Bourriea, J. L., Destee, A., & Guieu, J. D. (1996). Movement-related desynchronization pattern preceding voluntary movement in untreated Parkinson' s disease. Journal of Neurology, Neurosurgery and Psychiatry, 60, 307-312 https://doi.org/10.1136/jnnp.60.3.307
  6. Fuster, J. M. (1973). Unit activity in prefrontal cortex during delayed-response performance: Neuronal correlates of transient memory. Journal of Neurophysiology 36(1), 61-78
  7. Gagne, E. D., Yekovich, F. R., & Yekovich, C. W. (1997). The cognitive psychology of school learning(2nd ed). New York: Addison Wesley Longman, Inc
  8. Gasser, T., Von Lucadou-M?ller, 1., Verleger, R., & B?cher, P. (1983). Correlating EEG and IQ: A new look at an old problem using compuerized EEG parameters. EEG and Clinical Neurophysiology, 55, 493-504 https://doi.org/10.1016/0013-4694(83)90160-8
  9. Hur, M., Lawson, A. E., & Kwon, Y. (1997). The prefrontal lobes as a factorto constrain scientific reasoning ability. Journal of the Korean Association for Research in Science Teaching, 17, 525-540
  10. Jasper, J. J. (1958). The ten-twenty electrode system of the international federation. EEG and Clinical Neurophysiology, 10, 371-375
  11. Johnstone, A. H., Hogg, W. R., & Ziane, M. (1993). A working memory model applied to physics problem solving. International Journal of Science Education, 15, 663-672 https://doi.org/10.1080/0950069930150604
  12. Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive Science, 12, 1-48 https://doi.org/10.1016/0364-0213(88)90007-9
  13. Klimesch, W., Doppelmayr, M., Schimke, H., & Pachinger, T. (1996). Alpha frequency, reaction time, and the speed of processing information. Journal of Clinical, Neurophysiology, 13, 511-518 https://doi.org/10.1097/00004691-199611000-00006
  14. Kolb, B., & Whishaw, I. (1996). Human neurophychology (4th ed.). New York: W. H. Freeman and Company
  15. Kuhn, D., Amsel, E., & O'loughlin, M. (1988). The development of seientific thinking skills. San Diego, CA: Academic Press
  16. Kwon, Y., Yang, I., & Chung, W. (2000). An explorative analysis of hypothesis-generation by pre-service science teachers. Journal of the Korean Association for Research in Science Education, 20, 29-42
  17. Kwon, Y., Jeong, J. , Kang, M., & Kim, Y. (2003). A grounded theory on the process of generating hypothesis-knowledge about scientific episodes. Journal of the Korean Association for Research in Science Education, 23, 458-469
  18. Lawson, A. E. (1993). Deductive reasoning, brain maturation, and science concept acquisition: Are they linked? Journal of Research in Science Teaching, 30, 1029-1051
  19. Lawson, A. E. (1995). Science teaching and thedevelopment of thinking, Belmont, CA: Wadsworth Publishing Company
  20. Laxtha (2002). Complexity ver. 2.0 User Manual. Daejeon, Korea: Laxtha Inc
  21. Milner, G. A. (1963). Effects of different brain lesions on card sorting. Archives of Neurology, 9, 90-100 https://doi.org/10.1001/archneur.1963.00460070100010
  22. Milner, G. A. (1964). Some effects of frontal lobectomy in man. In J. M. Warren & K. Akert (Eds.), The frontal granular cortex and behavior (pp. 313-334). New York: McGraw-Hill
  23. Mirna, T., Oluwatimilehin, T., Hiraoka , T., & Hallett, M. (2001). Transient interhemispheric neuronal synchrony correlates with object recognition. The Journal of Neuroscience, 21, 3942-3948
  24. Niedermeyer, E., & Lopes da Silva, F. (1999). Electroencephalography: Basic principles, clinical applications, and related field. Baltimore, Maryland: Williams & Wilkins
  25. Robert, Jr. , R. J. , & Pennington, B. F. (1996). An interactive framework for examining prefrontal cognitive processes. Developmental Neuropsychology, 12, 105-126 https://doi.org/10.1080/87565649609540642
  26. Solso, R. L. (2001). Cognitive psychology (6th ed.). New York: Allyn & Bacon