• DocumentCode
    1852227
  • Title

    Student noncompletion factors and targeted resource allocation: a predictive model

  • Author

    Laing, Chris ; Robinson, Alan ; King, Graham

  • Author_Institution
    Technol. Fac., Southampton Inst., UK
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Abstract
    As an increasing higher priority, United Kingdom higher education institutions are introducing strategies to reduce student noncompletion rates. However, current measures of noncompletion make no allowance for the fluid characteristics of the higher education environment. Attention must be given to the characteristics of such an environment, and how this environment influences noncompletion. It is from this perspective that a preliminary model of the teaching and learning environment has been developed. It is proposed that the underlying nature of such an environment can be captured using a grounded theory methodology and implemented as a Bayesian vector auto regression model
  • Keywords
    Bayes methods; education; teaching; Bayesian vector auto regression model; United Kingdom; grounded theory methodology; higher education institutions; learning environment; predictive model; student noncompletion; targeted resource allocation; teaching environment; Bayesian methods; Councils; Current measurement; Econometrics; Economic forecasting; Education; Educational technology; Government; Predictive models; Resource management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontiers in Education Conference, 2001. 31st Annual
  • Conference_Location
    Reno, NV
  • ISSN
    0190-5848
  • Print_ISBN
    0-7803-6669-7
  • Type

    conf

  • DOI
    10.1109/FIE.2001.963661
  • Filename
    963661