Framework for identifying the most likely successful underprivileged tertiary study bursary applicants
In this paper, a decision support system framework is proposed that may be used to assist a tertiary bursary provider during the process of allocating bursaries to prospective students. The system identifies those in an initial pool of applicants who are expected to be successful tertiary students,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Stellenbosch University
2017-08-01
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| Series: | South African Journal of Industrial Engineering |
| Subjects: | |
| Online Access: | http://sajie.journals.ac.za/pub/article/view/1695 |
| _version_ | 1819133544614592512 |
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| author | Steynberg, Renier Lotter, Danie Van Vuuren, Jan Harm |
| author_facet | Steynberg, Renier Lotter, Danie Van Vuuren, Jan Harm |
| author_sort | Steynberg, Renier |
| collection | DOAJ |
| description | In this paper, a decision support system framework is proposed that may be used to assist a tertiary bursary provider during the process of allocating bursaries to prospective students. The system identifies those in an initial pool of applicants who are expected to be successful tertiary students, to facilitate final selection from a shortlist of candidates. The working of the system is based on various classification models for predicting whether bursary applicants will be successful in their respective tertiary studies. These model predictions are then combined in a weighted fashion to produce a final prediction for each student. In addition, a multi-criteria decision analysis method is used to assign each of the applicants to a ranking level. In this way, the system suggests both a predicted outcome for each candidate and a ranking according to which candidates may be compared. The practical working of the system is demonstrated in the context of real data provided by an industry partner, and the success rate of the system’s recommendations is compared with that of the industry partner. |
| first_indexed | 2024-12-22T09:48:59Z |
| format | Article |
| id | doaj.art-ab51569431494ab889e5a16bcb523665 |
| institution | Directory Open Access Journal |
| issn | 1012-277X 2224-7890 |
| language | English |
| last_indexed | 2024-12-22T09:48:59Z |
| publishDate | 2017-08-01 |
| publisher | Stellenbosch University |
| record_format | Article |
| series | South African Journal of Industrial Engineering |
| spelling | doaj.art-ab51569431494ab889e5a16bcb5236652022-12-21T18:30:26ZengStellenbosch UniversitySouth African Journal of Industrial Engineering1012-277X2224-78902017-08-01282597710.7166/28-2-1695Framework for identifying the most likely successful underprivileged tertiary study bursary applicantsSteynberg, Renier0Lotter, Danie1Van Vuuren, Jan Harm2Stellenbosch UniversityStellenbosch UniversityStellenbosch UniversityIn this paper, a decision support system framework is proposed that may be used to assist a tertiary bursary provider during the process of allocating bursaries to prospective students. The system identifies those in an initial pool of applicants who are expected to be successful tertiary students, to facilitate final selection from a shortlist of candidates. The working of the system is based on various classification models for predicting whether bursary applicants will be successful in their respective tertiary studies. These model predictions are then combined in a weighted fashion to produce a final prediction for each student. In addition, a multi-criteria decision analysis method is used to assign each of the applicants to a ranking level. In this way, the system suggests both a predicted outcome for each candidate and a ranking according to which candidates may be compared. The practical working of the system is demonstrated in the context of real data provided by an industry partner, and the success rate of the system’s recommendations is compared with that of the industry partner.http://sajie.journals.ac.za/pub/article/view/1695bursariesunderprivileged studentsstudy |
| spellingShingle | Steynberg, Renier Lotter, Danie Van Vuuren, Jan Harm Framework for identifying the most likely successful underprivileged tertiary study bursary applicants South African Journal of Industrial Engineering bursaries underprivileged students study |
| title | Framework for identifying the most likely successful underprivileged tertiary study bursary applicants |
| title_full | Framework for identifying the most likely successful underprivileged tertiary study bursary applicants |
| title_fullStr | Framework for identifying the most likely successful underprivileged tertiary study bursary applicants |
| title_full_unstemmed | Framework for identifying the most likely successful underprivileged tertiary study bursary applicants |
| title_short | Framework for identifying the most likely successful underprivileged tertiary study bursary applicants |
| title_sort | framework for identifying the most likely successful underprivileged tertiary study bursary applicants |
| topic | bursaries underprivileged students study |
| url | http://sajie.journals.ac.za/pub/article/view/1695 |
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