Student Funding Model Used By the National Student Financial Aid Scheme (Nsfas) at Universities in South Africa
Notice bibliographique
Résumé
Purpose: The purpose of this research is focused on evaluating NSFAS as student funding at South African Universities. Problem Investigated: Public universities in South Africa witnessed student protests on campuses during 2015 and 2016. These were orchestrated by students demanding additional funding assistance from the National Student Financial Aid Scheme (NSFAS), zero-fee increases and the scrapping of student debt by universities. In 2012 a report for fee-free university education for poor people was handed to the Minister of Higher Education and Training. It suggested that fee-free higher education would be possible if more funds were injected into the NSFAS. It is not currently known how much funding is required to fund both the poor students and the missing middle students who earn beyond the NSFAS eligibility threshold. Methodology: A quantitative research method was used. Information on student funding at a specific period, was collected using different universities to corroborate the data received in order to solve the research problem. The approach assisted in identifying how student funding is allocated per university in a specific academic year. Value of the research: The higher education sector is constantly evolving. The past struggle of universities was to ensure that they attracted the best academics and students. The focus has now changed to the student struggle on matters of academic exclusion, financial exclusion and the decolonizing of universities. The study of student funding in South African universities is made more urgent by student protests at universities, and the citing of lack of funding as the main reason why students have been excluded from the universities. The study focuses on the real impact on the universities and also how they have responded to the major challenges. Conclusion: Although this study focused mainly on student funding, it is critical that students who are funded from various sources are also supported in terms of psychological readiness, the transition from matric to university and acquiring financial management skills.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».