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Some Reasons Why Learning Science is Hard: Can Computer Based Law Encoding Diagrams Make It Easier?

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1452)

Abstract

Law EncodingDiagrams, LEDs, may be an effective approach to promotingconceptual learning in science. This paper considers why by decomposing the problem of what makes science hard to learn into five generaldifficulties. How LEDs may address each of these difficulties areconsidered in the context of a novel class of LEDs for electricity, AVOW diagrams. Further, thedesign requirements of ITSs that exploit LEDs can be analysed in terms of the difficulties, as illustrated by the description of the positivefeatures and limitations of a computer based learning environment that has been built to exploit AVOWdiagrams for learning about electricity.

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References

  1. 1.
    Anderson, J. R., Corbett, A., T., Koedinger, K., R., Pelletier, R.: Cognitive Tutors: Lessons Learned. The Journal Of The Learning Sciences, 4(2) (1995) 167–207CrossRefGoogle Scholar
  2. 2.
    Bechtel, W., Richardson, R. C.: Discovering complexity. Princeton University Press, Princeton, NJ (1991)Google Scholar
  3. 3.
    Cheng, P. C.-H.: Scientific Discovery with Law Encoding Diagrams. Creativity Research Journal 9(2&3) (1996) 145–162CrossRefGoogle Scholar
  4. 4.
    Cheng, P. C.-H.: Law Encoding Diagrams for Instructional Systems. Journal of Artificial Intelligence in Education 7(1) (1996) 33–74Google Scholar
  5. 5.
    Cheng, P. C.-H.: Learning Qualitative Relations in Physics with Law Encoding Diagrams. In: Cottrell G. (ed.): Proceedings of the 18th Annual Conference of the Cognitive Science Society. Lawrence Erlbaum, Hillsdale, NJ (1996) 512–517Google Scholar
  6. 6.
    Cheng, P. C.-H.: Interactive Law Encoding Diagrams for Learning and Instruction. Learning and Instruction (in press)Google Scholar
  7. 7.
    Cheng, P. C.-H., & Simon, H. A.: Scientific Discovery and Creative Reasoning with Diagrams. In: Smith, S., Ward, T., Finke, R. (eds.): The Creative Cognition Approach. MIT Press, Cambridge, MA. (1995) 205–228Google Scholar
  8. 8.
    Chi, M. T. H., Slotta, J. D., de Leeuw, N.: From things to processes: A Theory of Conceptual Change for Learning Science Concepts. Learning and Instruction. 4 (1994) 27–43CrossRefGoogle Scholar
  9. 9.
    Duit, R., Jung, W., & von Rhšneck, C. (eds.): Aspects of Understanding Electricity. Institute for the Pedagogy of Natural Science, University of Kiel (1984)Google Scholar
  10. 10.
    Egan, D. E., Schwartz, B. J.: Chunking in Recall of Symbolic Drawings. Memory and Cognition 7(2) (1979) 149–158Google Scholar
  11. 11.
    Halford, G.: Children’s Understanding. Lawrence Erlbaum, Hillsdale, NJ (1993)Google Scholar
  12. 12.
    Hewitt, P.: Conceptual Physics. 3rd ed. Harper Collins, New York, NY (1992)Google Scholar
  13. 13.
    Kotovsky, K., Hayes, J. R., Simon, H.A.: Why are Some Problems Hard? Cognitive Psychology 17 (1985) 248–294CrossRefGoogle Scholar
  14. 14.
    Larkin, J. H., Simon, H. A.: Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science 11 (1987) 65–99CrossRefGoogle Scholar
  15. 15.
    Lesgold, A., Lajoie, S., Bunzo, M., Eggan, G.: Sherlock: A Coached Practice Environment for an Electronics Troubleshooting Job. In: Larkin, J., Carboy, R. (eds.): Computer Assisted Instruction and Intelligent Tutoring Systems. Lawrence Erlbaum Associates, Hillsdale, NJ (1992) 201–238Google Scholar
  16. 16.
    Simon, H.A.: Sciences of the Artificial. 2nd ed. MIT Press, Cambridge, MA (1981)Google Scholar
  17. 17.
    Reif, F.: Interpretation of Scientific or Mathematical Concepts: Cognitive Issues and Instructional Implications. Cognitive Science 11 (1987) 395–416CrossRefGoogle Scholar
  18. 18.
    Slotta, J. D., Chi, M. T. H.: Understanding Constraint-Based Processes: A Precursor to Conceptual Change in Physics. In: Cottrell, G. W. (ed.): Proceedings of the 18th Annual Conference of the Cognitive Science Society. Lawrence Erlbaum, Hillsdale, NJ (1996) 306–311Google Scholar
  19. 19.
    White, B.: ThinkerTools: Causal Models, Conceptual Change, and Science Education. Cognition and Instruction 10(1) (1993) 1–100CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  1. 1.ESRC Centre for Research in Development, Instruction and Training, Department of PsychologyUniversity of NottinghamNottinghamUK

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