Journal of The Korean Association For Science Education (한국과학교육학회지)

The Korean Association for Science Education (한국과학교육학회)
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The Effects of Mental Capacity and Size of Chunk of Problem Solver and Mental Demand of Problem on Science Problem Solving

  • Published : 2002.12.30
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Abstract

The development of cognitive psychology provides us a theoretical base from which we can obtain information about human problem solving. One purpose of this study was to investigate the effects of cognitive psychological factors on the problem solving of the two kinds of tasks (content free, content specific). And the other purpose was to find out the existence of critical situation in problem solving process. Even the items of tasks with the same logical structure and content knowledge could have different sizes of mental demand. The results were as follows. The mental demand of the problem, and the problem solver's mental capacity, might be the main factors in problem solving. Critical situation of both a group and an individual existed in the tasks that need content free knowledge (FIT 752 task). But the critical situation of a group was completely different from that of the individual in the tasks that need content specific knowledge (electric circuit task). According to the analysis of achievement for each individual in the task that need content specific knowledge, the critical situation of an individual existed in problem solving, but the critical situation of a group was not existed by were summed up the individual results.

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References

  1. Anderson, J. R.(1980). Cognitive psychology and its Implication. W.H. Freeman and Company: Sanfrancisco, 282-288
  2. Burtis, P. J.(1982). Capacity increase and chunking in the development of short-term memory. Journal of Experimental Child Psychology, 34, 387-413 https://doi.org/10.1016/0022-0965(82)90068-6
  3. Case, R.(1978). A developmentally based theory and technology of instruction. Review of Educational Research, Summer, 48(3), 439-463
  4. Case, R.(1987). The structure and process of intellectual development, International Journal of Psychology, 22, 571-607 https://doi.org/10.1080/00207598708246796
  5. Chapman, M.(1990). Cognitive development and the growth of capacity: Issues, In J. T. Inns (Ed.), Neo-Piagetian theory in the development of attention: research and theory. Elsevier Science Publishers B. V.: North Holland, 263-287
  6. Demetriou, A,(1988). The neo-piagetian theories cognitive development: toward an integration. North Holland
  7. Frankel, M. T.(1989). Information processing approach, In D. F. Bjorklund (Ed.), Children's thinking developmental function and individual differences. Books/Cole Publishing Company: Pacific Grove California, 45-66
  8. Inhelder, B., & Piaget, J.(1958). The growth of logical thinking from childhood to adolescence. Basic Books, Inc.: New York
  9. Johnson, J. M.(1982). Manual for FIT: Figural Intersection Test
  10. Johnstone, A. H.(1990). Academic performance in solving chemistry problems related to student working memory capacity, International Journal of Science Education, 12(2), 177-185 https://doi.org/10.1080/0950069900120206
  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(6), 663-672 https://doi.org/10.1080/0950069930150604
  12. Niaz, M.(1980). The information-processing demand of chemistry problems and its relation to Pascual-Leone's functional M-capacity. International Journal of Science Education, 10(2), 231-238
  13. Niaz, M.(1987). Relation between M-space of students and M-demand of different items of general chemistry and its interpretation based upon the Neo-Piagetian theory of Pascual- Leone. Journal of Chemical Education, 64(6), 502-505 https://doi.org/10.1021/ed064p502
  14. Niaz, M.(1989). Relation between Pascual-Leone's structural and functional M-space and its effect on problem solving in chemistry, International Journal of Science Education, 11(1), 93-99 https://doi.org/10.1080/0950069890110109
  15. Niaz, M.(1990). The relationship between M-demand, algorithms, and problem solving: A Neo- Piagetian analysis, Journal of Chemical Education, 422-424
  16. Niaz, M.(1992). Manipulation of logical structure of chemistry problem and its effect on student performance. Journal of Research in Science Teaching, 29(3), 211-226 https://doi.org/10.1002/tea.3660290303
  17. Niaz, M., & Lawson, A. E.(1985). Balancing chemical equations: The role of developmental level and mental capacity, Journal of Research in Science Teaching, 22(1), 41-51 https://doi.org/10.1002/tea.3660220104
  18. Opdenacker.C., Fierens, H., Van Brabant, H., Sevenants, J., Spruyt, J., Slootmakers, P.J., & Johnstone, A. H.(1980). Academic performance in solving chemistry problems related to student working memory capacity, International Journal of Science Education, 12(2). 177- 185 https://doi.org/10.1080/0950069900120206
  19. Pascual-Leone, J.(1970). A mathematical model for the transition rule in Piaget's developmental stages. Acta Psychologies, 32, 301-345 https://doi.org/10.1016/0001-6918(70)90108-3
  20. Pascual-Leone, J.(1987). Organismic processes for neo-Piagetian theories: a dialectical causal account of cognitive development, International Journal of Psychology, 22, 531-570 https://doi.org/10.1080/00207598708246795
  21. Roth, W. M.(2000). Artifical Networks for Modeling Knowing and Learning in Science. Journal of Research in Science Teaching. 37(1), 63-80 https://doi.org/10.1002/(SICI)1098-2736(200001)37:1<63::AID-TEA5>3.0.CO;2-H
  22. Rutherford, M.(1997). Working Memory revisited: can we use it to select science student. International Journal of Science Education, 19(8), 939-955 https://doi.org/10.1080/0950069970190807
  23. Simon, H. A.(1974). How big is a chunk?. Science, 183,482-488 https://doi.org/10.1126/science.183.4124.482
  24. Ahn, S-Y., Kwon, J-S.(1995). Psychological Approach on Common Core of Misconceptions by Pascual-Leone's neo Piagetian Theory. Journal of the Korea Association for Research in Science Education. 15(2), 185-193
  25. Ahn, S-Y., Kwon, J-S.(1995). The Effect on Problem solving According to Mental Demand of Items and Chunking, Journal of the Korea Association for Research in Science Education. 15(3), 263-273
  26. Tsaparlis, G. (1998). Dimensional analysis and predictive models in problem solving. International Journal of Science Education, 20(3), 335-350 https://doi.org/10.1080/0950069980200306