Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution
The Admission Point Score (APS) is used by most South African universities to identify a university programme in which a learner is likely to succeed. While the APS appears helpful to gauge the aptitude of a learner and predict their success, the reality is that between 2008 and 2015 almost 50% of l...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
South African Institute of Computer Scientists and Information Technologists
2022-12-01
|
| Series: | South African Computer Journal |
| Online Access: | https://sacj.cs.uct.ac.za/index.php/sacj/article/view/832 |
| _version_ | 1811190105802539008 |
|---|---|
| author | Ritesh Ajoodha |
| author_facet | Ritesh Ajoodha |
| author_sort | Ritesh Ajoodha |
| collection | DOAJ |
| description | The Admission Point Score (APS) is used by most South African universities to identify a university programme in which a learner is likely to succeed. While the APS appears helpful to gauge the aptitude of a learner and predict their success, the reality is that between 2008 and 2015 almost 50% of learners who made the required APS for a Science programme failed to complete the requirements for that programme. This paper delineates and diagnoses learner vulnerability, using a learner attrition model, for early intervention and as an alternative to using the APS. The analysis shows that various predictive models achieve higher accuracy to predict learner vulnerability, by incorporating factors of the learner attrition model, rather than just using the APS score. This paper argues for a more complex view of predicting learner vulnerability for early interventions by incorporating the learner's background, individual characteristics, and schooling data. It does not agree with the aggregation of National Senior Certificate (NSC) subjects into APS scores since this normalises the complexity of the subtle relations between the schooling system, learner attrition, and pre-schooling pedagogical dynamics. This paper points to a more nuanced view of predicting learner vulnerability. |
| first_indexed | 2024-04-11T14:44:47Z |
| format | Article |
| id | doaj.art-317db62f34d343fea16edced593139ae |
| institution | Directory Open Access Journal |
| issn | 1015-7999 2313-7835 |
| language | English |
| last_indexed | 2024-04-11T14:44:47Z |
| publishDate | 2022-12-01 |
| publisher | South African Institute of Computer Scientists and Information Technologists |
| record_format | Article |
| series | South African Computer Journal |
| spelling | doaj.art-317db62f34d343fea16edced593139ae2022-12-22T04:17:40ZengSouth African Institute of Computer Scientists and Information TechnologistsSouth African Computer Journal1015-79992313-78352022-12-0134210.18489/sacj.v34i2.832747Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institutionRitesh Ajoodha0University of the Witwatersrand, JohannesburgThe Admission Point Score (APS) is used by most South African universities to identify a university programme in which a learner is likely to succeed. While the APS appears helpful to gauge the aptitude of a learner and predict their success, the reality is that between 2008 and 2015 almost 50% of learners who made the required APS for a Science programme failed to complete the requirements for that programme. This paper delineates and diagnoses learner vulnerability, using a learner attrition model, for early intervention and as an alternative to using the APS. The analysis shows that various predictive models achieve higher accuracy to predict learner vulnerability, by incorporating factors of the learner attrition model, rather than just using the APS score. This paper argues for a more complex view of predicting learner vulnerability for early interventions by incorporating the learner's background, individual characteristics, and schooling data. It does not agree with the aggregation of National Senior Certificate (NSC) subjects into APS scores since this normalises the complexity of the subtle relations between the schooling system, learner attrition, and pre-schooling pedagogical dynamics. This paper points to a more nuanced view of predicting learner vulnerability.https://sacj.cs.uct.ac.za/index.php/sacj/article/view/832 |
| spellingShingle | Ritesh Ajoodha Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution South African Computer Journal |
| title | Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution |
| title_full | Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution |
| title_fullStr | Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution |
| title_full_unstemmed | Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution |
| title_short | Identifying academically vulnerable learners in first-year science programmes at a South African higher-education institution |
| title_sort | identifying academically vulnerable learners in first year science programmes at a south african higher education institution |
| url | https://sacj.cs.uct.ac.za/index.php/sacj/article/view/832 |
| work_keys_str_mv | AT riteshajoodha identifyingacademicallyvulnerablelearnersinfirstyearscienceprogrammesatasouthafricanhighereducationinstitution |