• DocumentCode
    2589385
  • Title

    Enrollment forecasting for an upper division general education component

  • Author

    Choudhuri, Shabbir ; Standridge, Charles R. ; Griffin, Carol ; Wenner, Wendy

  • Author_Institution
    Coll. of Eng. & Comput., Grand Rapids
  • fYear
    2007
  • fDate
    10-13 Oct. 2007
  • Abstract
    An administration-engineering partnership was established to ensure the effective operation of an upper division, general education theme requirement at Grand Valley State University (GVSU). The percent of theme course seats occupied was increasing each semester and approaching 100%. Student complaints about course unavailability and other anecdotal evidence supported the quantitative evidence. A regression analysis, based on historical enrollment data, provided an accurate forecast of the number of students enrolled by semester and level, freshman through senior. A second regression analysis yielded equations for the number of theme courses taken by students at each level in each semester. The coefficient of determination (R2) was 94.5% or above for each semester for juniors and seniors who are the vast majority of students in theme courses. Since resources for expanding theme courses offerings by the forecasted 23% were not available, existing courses were reviewed for their applicability to each theme and numerous of these were added for the 2005-2006 academic year. Academic year 2006-2007 theme courses enrollment is 93% of capacity. The number of student complaints concerning theme course unavailability is perceived to have dropped.
  • Keywords
    educational courses; educational institutions; regression analysis; Grand Valley State University; administration-engineering partnership; course unavailability; enrollment forecasting; historical enrollment data; regression analysis; student complaints; theme courses; upper division general education component; Data analysis; Demand forecasting; Drives; Educational institutions; Educational programs; Equations; Operations research; Predictive models; Regression analysis; Technological innovation; Enrollment forecasting; general education; institutional data analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontiers In Education Conference - Global Engineering: Knowledge Without Borders, Opportunities Without Passports, 2007. FIE '07. 37th Annual
  • Conference_Location
    Milwaukee, WI
  • ISSN
    0190-5848
  • Print_ISBN
    978-1-4244-1083-5
  • Electronic_ISBN
    0190-5848
  • Type

    conf

  • DOI
    10.1109/FIE.2007.4417877
  • Filename
    4417877