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Learning-Testing Process in Classroom: An Empirical Simulation Model

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  • Buda, Rodolphe

Abstract

This paper presents an empirical micro-simulation model of the teaching and the testing process in the classroomH. It is a non-econometric micro-simulation model describing informational behaviors of the pupils, based on the observation of the pupils’ communication behavior during lessons and tests. The representation of the knowledge process is very simplified. However, we tried to study the involvements of individual motivation, capability and relationship with other pupils of each pupil, to compare them to the new-classical(and keynesian) and Austrian information and knowledge theoretical results. It is a first step and future development should concern expectation behaviors and dynamics. This paper aims too to give, we hope so, some criteria of pupils’ rationality in the classroom.

Suggested Citation

  • Buda, Rodolphe, 2009. "Learning-Testing Process in Classroom: An Empirical Simulation Model," MPRA Paper 12146, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:12146
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    File URL: https://mpra.ub.uni-muenchen.de/12146/1/MPRA_paper_12146.pdf
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    References listed on IDEAS

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    1. Steven G. Rivkin & Eric A. Hanushek & John F. Kain, 2005. "Teachers, Schools, and Academic Achievement," Econometrica, Econometric Society, vol. 73(2), pages 417-458, March.
    2. Mary A. Burke & Tim R. Sass, 2013. "Classroom Peer Effects and Student Achievement," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 51-82.
    3. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 322-322.
    4. Boettke, Peter J, 2002. "Information and Knowledge: Austrian Economics in Search of its Uniqueness," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 15(4), pages 263-274, December.
    5. Lisa R. Anderson & Charles A. Holt, 1996. "Classroom Games: Information Cascades," Journal of Economic Perspectives, American Economic Association, vol. 10(4), pages 187-193, Fall.
    6. Buda, Rodolphe, 1999. "Quantitative Economic Modeling vs Methodological Individualism ?," MPRA Paper 4004, University Library of Munich, Germany.
    7. Joe Kerkvliet & Charles L. Sigmund, 1999. "Can We Control Cheating in the Classroom?," The Journal of Economic Education, Taylor & Francis Journals, vol. 30(4), pages 331-343, December.
    8. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    9. Thierry Aimar, 2008. "Self-ignorance: Towards an extension of the Austrian paradigm," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 21(1), pages 23-43, March.
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    11. Macho-Stadler, Ines & Perez-Castrillo, J. David, 2001. "An Introduction to the Economics of Information: Incentives and Contracts," OUP Catalogue, Oxford University Press, edition 2, number 9780199243273.
    12. Jaag, Christian, 2006. "A Simple Model of Educational Production," MPRA Paper 338, University Library of Munich, Germany.
    13. Brauer, Jurgen & Delemeester, Greg, 2001. " Games Economists Play: A Survey of Non-computerized Classroom-Games for College Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 15(2), pages 221-236, April.
    14. Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947 Elsevier.
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    More about this item

    Keywords

    Teaching ; Learning ; Cheating ; Information ; Communication ; Knowledge ; Micro-simulation ; Classroom;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • A2 - General Economics and Teaching - - Economic Education and Teaching of Economics
    • B53 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Austrian

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