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Detecting Code Evolution in Programming Learning

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Advances in Artificial Intelligence - SBIA 2008 (SBIA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5249))

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Abstract

This article describes a research in code evolution for programming learning that has as its main components the identification of the specific demands for detecting code evolution in the context of programming learning, and the identification of an initial set of programming learning supporting strategies. The findings within the knowledge represented in the codes allowed us to carry out a deeper analysis concerning the inferences internal to the code strategy, which is especially useful for exploring the supporting strategies and the techniques students normally use for their knowledge acquisition in programming.

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Author information

Authors and Affiliations

  1. Department of Informatics (PUC-Rio), R. Marquês de S. Vicente, 225 RDC – Gávea, 22453-900, Rio de Janeiro, RJ, Brazil

    Thais Castro & Hugo Fuks

  2. Computer Science Department (UFAM), Av. Gal. R. O. J. Ramos, 3000, 69077-300, Manaus, AM, Brazil

    Thais Castro & Alberto Castro

Authors
  1. Thais Castro
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  2. Hugo Fuks
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  3. Alberto Castro
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Editor information

Editors and Affiliations

  1. Department of Systems Engineering and Computer Science - COPPE, Federal University of Rio de Janeiro (UFRJ), Brazil

    Gerson Zaverucha

  2. Department of Automation and Systems, Federal University of Santa Catarina, CEP 88.040-900, Brazil

    Augusto Loureiro da Costa

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© 2008 Springer-Verlag Berlin Heidelberg

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Castro, T., Fuks, H., Castro, A. (2008). Detecting Code Evolution in Programming Learning. In: Zaverucha, G., da Costa, A.L. (eds) Advances in Artificial Intelligence - SBIA 2008. SBIA 2008. Lecture Notes in Computer Science(), vol 5249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88190-2_20

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  • DOI: https://doi.org/10.1007/978-3-540-88190-2_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88189-6

  • Online ISBN: 978-3-540-88190-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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