• DocumentCode
    351381
  • Title

    Pretesting and data modeling for forecasting student success in computer science courses

  • Author

    Surkan, Alvin J.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Nebraska Univ., Lincoln, NE, USA
  • Volume
    1
  • fYear
    1999
  • fDate
    10-13 Nov. 1999
  • Abstract
    An experimental study in the design and use of questionnaires aims to capture salient information for predicting student success for computer science courses. Developing uniform and easy-to-use methods for collecting and processing information on student ability and preparation is the main objective. Such methods must be robust with respect to missing data. It should be influenced minimally by differences of cultural backgrounds and language proficiency.
  • Keywords
    computer science education; computer science courses; data modeling; information collection; information processing; missing data; pretesting; questionnaires design; questionnaires use; student ability; student success forecasting; Biological cells; Computer architecture; Computer networks; Computer science; Genetic algorithms; Optimization methods; Predictive models; Problem-solving; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontiers in Education Conference, 1999. FIE '99. 29th Annual
  • Conference_Location
    San Juan, Puerto Rico
  • ISSN
    0190-5848
  • Print_ISBN
    0-7803-5643-8
  • Type

    conf

  • DOI
    10.1109/FIE.1999.839170
  • Filename
    839170