Die voorspelling van akademiese sukses by eerstejaar-technikonstudente

[摘要] English: The shortage of high-level person power is a world-wide problem. Seriouseconomic problems are also experienced in South Africa as a result of this. Highereducation plays a central role in meeting South Africa's social and economicneeds. The Department of Education sets broad higher education objectives thatregard the transformation of higher education as part of South Africa's pursuit ofsocial justice and progress of the economy as a whole. The relation betweenhigher education and South Africa's economic and socialprogress was explained inthis study within the framework of the general systemstheory.In the pursuit of achieving higher educational institution objectives, highereducational institutions frequently use selection processes. The challenge thathigher educational institutions are currently facing is to develop selection modelsthat will succeed in identifying talented individuals and in effectively predictingfuture academic success. The problem regarding selection is complex in amulticultural country like South Africa, because unequal opportunities anddifferent backgrounds are substantial realities. New selection models must bedeveloped to accommodatethe changing cultural composition of South Africa. As Technikon Free State is confronted with overwhelming numbers of studentsand unequal backgrounds, a new selection model was used which takes intoaccount general scholastic aptitude as measured by the General ScholasticAptitude Test (GSAT),language skills as measured by the English Proficiency Test(EPT),and the number of subjects for which students registered.The problem statement of this study is the determination of a selection model thatcould predict possible academic success for first-year technikon students. Thisstudy determines to what extent the predictor variables, namely matric results,GSAT-counts,EPT-countsand the number of subjects for which students registercan be utilised to predict the criterion variable, namely academic success, in the Faculties of Management, Engineering, Human Science and Applied Sciences. Astep-wise regression analysis was done to determine the above.It appeared from the results that matric performance was the variable thatcorrelated most highly with academic success. This trend was indicated mainly forthe total group. The regression equation indicated that this variable correctlypredicted approximately 13 % of the total variance of the criterion variable.

[发布机构] University of the Free State