Prediction of academic success of first year students. The recent amalgamation of the various regional education systems in South Africa and as a result/ the restructuring of the education dispensation, led to a number of problems which impacted negatively on the examination process. Against this backdrop, the present study attempted to find a valid altermative for matric marks as a predictor of academic success. Multiple regression analyses and canonical discriminant analyses were performed to construct a comprehensive model, which can be used to predict the academic achievement of students, and serve as an alternative for matric marks. Regression analyses with average exam mark as criterion were performed on the data of the three largest faculties. Multiple correlations of 0,59, 0,56 and 0,52 were obtained. Discriminant analyses were done against a promotion criterion (promoted,not promoted), for each of the faculties. According to the results of the discriminant analyses the percentage correct classifications varied from 62,7% to 81,1%.
Opsomming Die onlangse samesmelting van die onderskeie streeksonderwysstelsels in Suid-Afrika en die gevolglike herstrukturering van die onderwys, het sy eie kwota probleme opgelewer wat 'n negatiewe impak op matriekeksaminering gehad het. Teen hierdie agtergrond het die huidige studie gepoog om 'n geldige alternatief vir matriekpunte as voorspeller van akademiese prestasie te vind. Meervoudige regressie-ontledings asook kanoniese diskriminantontledings is op die datastel uitgevoer ten einde 'n omvattende model daar te stel waarmee die akademiese prcstasie van studente voorspel kan word, en wat as plaasvervanger vir matriekpunte kan dien. regressie- ontledings vir die drie grootste fakulteite is gedoen met die gemiddelde eksamenpunt as kriterium. Meervoudige korrelasies van 0,59, 0,56 en 0,52 is verkry. Diskriminantontledings is vir elke fakulteit teenoor 'n promosiekriterium (promoveer/nie-promo-veer) uitgevoer. Volgens die resultate van die diskriminantontledings het die persentasie korrekte klassifikasies gewissel van 62,7% tot 81,1%
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