Doctoral Degrees (Statistics and Actuarial Science)

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Browsing Doctoral Degrees (Statistics and Actuarial Science) by browse.metadata.advisor "Le Roux, Niel Johannes"

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    A statistical analysis of student performance for the 2000-2013 period at the Copperbelt University in Zambia
    (Stellenbosch : Stellenbosch University, 2017-12) Ngoy, Mwanabute; Le Roux, Niel Johannes; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science.
    ENGLISH SUMMARY : Education in general, and tertiary education in particular are the engines for sustained development of a nation. In this line, the Copperbelt University (CBU) plays a vital role in delivering the necessary knowledge and skills requirements for the development of Zambia and the neighbouring Southern Africa Region. It is thus important to investigate relationships between school and university results at the CBU. The first year and the graduate datasets comprising the CBU data for the 2000-2013 period were analysed using a geometric data analysis approach. The population data of all school results for the whole Zambia from 2000 to 2003 and from 2006 to 2012 were also used. The findings of this study show that the changes in the cut-off values for university entrance resulted in the CBU admitting school leavers with better school results, i.e. most recent intakes of first year students had higher school results than the older intakes. But the adjustment on the cut-off values did not have a major effect on the university performance. There was a general tendency for students to achieve higher scores at school level which could not translate necessarily into higher academic achievement at university. Additionally, certain school subjects (i.e. school Mathematics, Science, Physics, Chemistry, Additional Mathematics, Geography, and Principles of Accounts) and the school average for all school subjects were identified as good indicators of university performance. These variables were also found to be responsible for the group separation/discrimination among the four groups of the first year students. For graduate students, the school average was the major determinant of the degree classification. However, most school variables had limited discrimination power to differentiate between successful and unsuccessful students. Furthermore, it was found that policies of making school results available as grades rather than actual percentages can have a marked influence on expected university achievements. One of the major contributions of this thesis is the use of optimal scores as an alternative imputation method applicable to interval-valued and categorical data. This study also identified years of study which needed more focus in order to enhance the performance of students: the first two years of study for business related programmes, the third year of study for engineering programmes, and the third and fifth year of study for other programmes. Additionally, the study also identified certain school variables which were good indicators of university performance and which could be used by the university to admit potential successful students. It was also found that the first year Mathematics had the worst performance at the first year level despite the students achieving outstanding results in school Mathematics. It was also found that a clear demarcation exists between the “clear pass” (CP) students, i.e. those who successfully passed the first year of study and other first year groups. Also the “distinction” (DIS) group, i.e. those who completed their undergraduate studies with distinction, was apart from the other groups. These two groups (CP and DIS groups) mostly achieved outstanding results at school level as compared to other groups.