Modelling Continuing Load at Disaggregated LevelsReport as inadecuate




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Journal of Institutional Research, v19 n1 p55-63 Jul 2014

The current methodology of estimating load in the following year at Flinders University has achieved reasonable accuracy in the previous capped funding environment, particularly at the university level, due largely to our university having stable intakes and student profiles. While historically within reasonable limits, variation in estimates at the course level is increasing due to the removal of the capped environment, increased competitiveness across universities, and changing student composition, profiles, and study patterns. This translates to uncertainty in funding and how it is distributed across courses. It is now necessary to predict load in a way that accommodates the changing higher education landscape, with greater accuracy at the course level. This article compares the current method of estimating continuing load in the following year with an alternative method developed by the Planning Services Unit. The current method creates one estimate per course and utilises the previous year's continuation rate unless exogenous information suggests otherwise. The proposed alternative method disaggregates courses according to student academic characteristics that are associated with continuation rates. The method uses a generalised linear statistical model, derived from varying amounts of historic data, to estimate continuing load separately within each course cross-classification. This article will describe the logistics associated with, and the benefits of, applying the new method when predicting continuing load in Funding Group 1 (Commonwealth supported load) in 2013.

Descriptors: Foreign Countries, Educational Finance, Financial Support, Resource Allocation, Higher Education, Computation, Planning, Student Characteristics, Prediction, Enrollment Trends, Grade Point Average, Age, Gender Differences, Regression (Statistics), Models, Full Time Students, Full Time Equivalency

Australasian Association for Institutional Research. 546 Gallymont Road, Mandurama, NSW 2792, Australia. +61-2-6367-5347; e-mail: secretary[at]aair.org.au; Web site: http://www.aair.org.au





Author: Seidel, Ewa

Source: https://eric.ed.gov/?q=a&ft=on&ff1=dtySince_1992&pg=3114&id=EJ1060091



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