• DocumentCode
    3637662
  • Title

    Evaluating Student Response Driven Feedback in a Programming Course

  • Author

    José Luis Fernández Alemán;Dominic Palmer-Brown;Chrisina Draganova

  • Author_Institution
    Fac. of Comput. Sci., Univ. of Murcia, Murcia, Spain
  • fYear
    2010
  • Firstpage
    279
  • Lastpage
    283
  • Abstract
    This paper presents an experience of generating diagnostic feedback for guided learning in an introductory programming course. An on-line Multiple Choice Questions (MCQs) system is integrated with a neural network based data analysis. Some empirical results about how students use the system in a CS1 course are presented. Research with an experimental group of 61 students suggests that the feedback addresses the level of knowledge of the individual and guides them towards a greater understanding of particular concepts. Moreover the approach proposed promotes the students´ interest and produces statistically significant differences in the scores between the experimental group and control group.
  • Keywords
    "Artificial neural networks","Electronic learning","Training","Programming profession","Instruments"
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies (ICALT), 2010 IEEE 10th International Conference on
  • Print_ISBN
    978-1-4244-7144-7
  • Type

    conf

  • DOI
    10.1109/ICALT.2010.82
  • Filename
    5571312