Department of Industrial Psychology

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Browsing Department of Industrial Psychology by Subject "Academic performance"

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    Validation of a selection battery used by the South African Military Academy
    (Stellenbosch : University of Stellenbosch, 2010-12) Pretorius, Marlize; Redelinghuys, Marlize; Theron, C. C.; University of Stellenbosch. Faculty of Economic and Management Sciences. Dept. of Industrial Psychology
    ENGLISH ABSTRACT: The objective of this study is to determine whether the psychometric evaluation procedure, used by the South African Military Academy to make selection decisions, can validly predict academic performance of first year learners, whether this procedure is fair and whether the procedure is efficient. The sample used for this study consisted of three year groups (First Year Students of 2001, 2002 and 2003) enrolled at the Military Academy. In theory specific learning behaviours (learning competencies) are instrumental in attaining academic performance. These learning behaviours, in turn, depend on and are expressions of a complex nomological network of person-centered characteristics (learning competency potential). Differences in learning performance can be explained in terms of learning behaviours. Learning competencies are instrumental in achieving the learning outcomes for which the academic programme exists. Learning competencies, in turn, can be explained in terms of learner characteristics. In order to differentiate between candidates who have better or poorer training prospects in terms of a construct orientated approach to selection, a performance hypothesis on the person-centered drivers of the learning competencies is used. It is argued that the degree of competence in: (1) the core cognitive processes/competencies that constitute learning (transfer and automatization) and are necessary to create meaningful structure in novel learning material, (2) the intellectual drivers of these learning competencies (fluid intelligence and information processing capacity), (3) proficiency in English and (4) past academic performance, should discriminate between better or poorer academic performance of learners attending the academic programmes at the SA Military Academy. The grade point average of the first year first semester academic results is used as a measure of the criterion construct. Almost all of the results obtained in this study support the theory and propositions made by the performance hypothesis. Only one variable, accuracy of information processing, did not perform as predicted by the performance hypothesis. Prior learning explained the most variance in the criterion (r=0,4312). The inter-correlation amongst the predictors is used to infer the proportion of unique variance each predictor accounts for in the composite criterion. A regression of the composite criterion on the array of predictors (X2 – X12) revealed that only memory and understanding (X9) and prior learning (X12) uncovered relevant and unique information about determinants of performance on the criterion not conveyed by the remaining predictors in the model. The remaining predictors in the selection battery can consequently be considered redundant since they provide no new information not already conveyed by X9 and X12. When YGPA is regressed on the weighted combination of X9 and X12, only X12 significantly explains unique variance in YGPA when included in a regression model already containing X9. In the light of the reported findings there is no need to create a combined weighted linear predictor composite (Xcomp) which would form the basis of the actuarial mechanical decision rule that would guide selection decisions. Prior learning proved to be the only predictor that warrants inclusion in the actuarial mechanical prediction rule that will form the basis of selection decisions. In terms of the derived actuarial prediction rule the expected criterion performance of all applicants (E[Y|X12]) could consequently be estimated by inserting the measures obtained during selection of prior learning into the derived regression equation. The use of this equation could be regarded as permissible to the extent to which E[Y|X12] correlates significantly with YGPA. Since E[Y|X12] correlates 0,431 and statistically significantly (p<0,05) with YGPA, the predictions derived from this equation are valid. The findings of this research suggest that black and white students were sampled from the same population and therefore the use of the single, undifferentiated prediction rule would lead to fair selection decisions. To answer the question whether the selection procedure under investigation is adding any value to the organization, utility analysis is done based on the Taylor-Russell utility model as well as the Naylor-Shine interpretation of selection utility. A criterion-referenced norm table that expresses the risk of failure conditional on expected academic performance is derived from the use of only X12. Recommendations for further research are put forward.