From my own experience working in Institutional Research for the past seven years, there is not a proper, reliable, and comprehensive model for forecasting student enrolment quickly. In many funding formulas, enrolment is the main driver of government grants and student tuition fees, which are sources of income to the university. Existing enrolment management tools developed within Institutional Research departments tend to be “ad hoc” spreadsheets with multiple individuals manipulating them with the result that the output comes too late for departments to take remedial action in terms of their budgets and does not provide multiple scenarios in support of strategic decision-making. The purpose of this study is to describe a functional automated enrolment projection system methodology I developed from scratch through a case study of the Faculty of Arts & Science at the University of Toronto. My primary research was to actually build the model. The model in effect, is the thesis. The system provides multiple scenarios that allow senior management in a multi-campus university system to generate multiple income scenarios, enabling them to make well-informed decisions concerning the operation of their institution and timely calculation and allocation of resources to academic departments. The study then shows how this addresses the problems of “ad hoc” approaches, and how it may be applied in other situations.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/29726 |
| Date | 30 August 2011 |
| Creators | Gasteiger, David William |
| Contributors | Lang, Daniel W. |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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