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Time-to-degree: identifying factors for predicting completion of four year undergraduate degree programmes in the built environment at the University of Witwatersrand

A research report submitted to Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science, 2012. / The study aims to identify the variables which best predict completion of four year undergraduate degree programmes, in the Schools of Construction Economics and Management and Architecture and Planning, at the University of Witwatersrand (Wits) in South Africa. The research is important to the University and in particular the schools under investigation, because there are only a few studies done in South African universities on this topic and it will contribute to the knowledge on variables that positively influence Time-to-Degree. Selected demographic variables such as Gender, Race, and Home Language were analysed. Other variables considered include: University Courses, First Year Scores, Matric Aggregate, Financial Aid and Residence Status.
The Binary Logistic Models, a Multinomial Logistic Model and Classification Tree Model were developed to test for the significance of the predictor variables at 5% level of significance. The Statistical packages that were used in the analysis of data are Statistical Package for Social Sciences (SPSS), Statistical Analysis System (SAS).
The logistic regression models indicated that Home Language is English and the first year university course Building Quantities 1 are the most important predictors of Time-to-Degree. The other variables that were significant are Gender is Female, Not Repeat, Theory & Practice of QS 1, Architectural Representation I, Building Quantities 1, Construction Planning and Design, Physics Building and Planning for Property Developers. Architectural Representation I, Building Quantities 1, Construction Planning and Design, Physics Building and Planning for Property Developers. Matric Aggregate is an important predictor of university first year success though it has no impact on TTD. The Classification Tree indicated that passing first year at university was significant as it increases the chances of completing the degree programme within the minimum time.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/12697
Date29 April 2013
CreatorsMamvura, Innocent
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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