Challenges of Student Selection: Predicting Academic Performance
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| Title: | Challenges of Student Selection: Predicting Academic Performance |
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| Language: | English |
| Authors: | van der Merwe, D., de Beer, M. |
| Source: | South African Journal of Higher Education. 2006 20(4):547-562. |
| Availability: | Unisa Press. Preller Street, P.O. Box 392, Muckleneuk, Pretoria 0003, South Africa. Tel: +27-24-298960; Fax: +27-24-293449; e-mail: sajhe@vodamail.co.za; Web site: http://www.sajhe.org.za |
| Peer Reviewed: | Y |
| Page Count: | 16 |
| Publication Date: | 2006 |
| Document Type: | Journal Articles Reports - Evaluative |
| Education Level: | Higher Education |
| Descriptors: | Disadvantaged, Academic Achievement, Predictive Validity, Admission Criteria, Psychometrics, Cognitive Ability, Robustness (Statistics), Goodness of Fit, Scoring Rubrics, Evaluation Problems, Longitudinal Studies, Predictor Variables, Correlation |
| Geographic Terms: | South Africa |
| ISSN: | 1011-3487 |
| Abstract: | Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the under preparedness of students necessitates that their potential cognitive abilities should be assessed rather than their current abilities. In predicting their academic performance, it is argued that conventional psychometric tests are less suitable for the selection of students from disadvantaged backgrounds, because they are a static measure of current abilities which gives no indication of the student's potential to learn when in an optimum environment. The predictive validity of the Potential Index Battery, the Learning Potential Computerised Adaptive Test and school-leaving results in selection, were determined by calculating the correlation of these measures with academic performance over the full duration of the students' studies. Statistically significant correlations were found, thus indicating that the learning potential test had higher predictive powers than static measures of cognitive ability and school-leaving results, in predicting future academic performance. (Contains 6 tables and 2 notes.) |
| Abstractor: | As Provided |
| Number of References: | 45 |
| Entry Date: | 2009 |
| Access URL: | https://www.sajhe.org.za/ |
| Accession Number: | EJ852714 |
| Database: | ERIC |
| Abstract: | Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the under preparedness of students necessitates that their potential cognitive abilities should be assessed rather than their current abilities. In predicting their academic performance, it is argued that conventional psychometric tests are less suitable for the selection of students from disadvantaged backgrounds, because they are a static measure of current abilities which gives no indication of the student's potential to learn when in an optimum environment. The predictive validity of the Potential Index Battery, the Learning Potential Computerised Adaptive Test and school-leaving results in selection, were determined by calculating the correlation of these measures with academic performance over the full duration of the students' studies. Statistically significant correlations were found, thus indicating that the learning potential test had higher predictive powers than static measures of cognitive ability and school-leaving results, in predicting future academic performance. (Contains 6 tables and 2 notes.) |
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| ISSN: | 1011-3487 |
