Staking van studie aan landbou-opleidingsinstellings in die Wes-Kaap : waarskynlike oorsake en strategiee vir students-ondersteuning
Bibliographic record
Abstract
Student dropout at higher education institutions in South Africa is an aspect that is receiving increasing attention from the various role-players who have an interest in this aspect due to the negative influence it has on students, higher education institutions, and the economy of the country. Higher education institutions that offer agriculture as a course of study also have to deal with this problem. Approximately one quarter of the students who are admitted at most agricultural training institutions are forced to discontinue their studies or do so voluntarily. Most of these cessations of study occur during or near the end of the first year of study. The cessation of studies is not the only negative aspect. The low pass rate of students at higher education institutions in South Africa is also alarming. The main object of this study was to ascertain why students discontinued their studies and why they took longer than the minimum time allowed to complete their studies. In order to substantiate this theory, an attempt was made to obtain both an international and a national perspective of the student dropout rate in general, as well as to determine what factors were responsible or contributed to successful completion of their studies by students. A background perspective of agricultural education in South Africa was included. The literature reviews are supplemented by a qualitative investigation of students who discontinued their studies specifically at agricultural higher education institutions. A case study approach was employed, in which an in-depth interview strategy was utilised to obtain descriptive and illustrative data. The study demonstrated that dropout rates can be attributed mainly to academic and/or social factors. These factors prevented adequate integration, which is essential to successful studies, from occurring. Various academic factors may be the reason for inadequate academic integration, of which the most important were unclear objectives, a lack of motivation, wrong academic expectations, a misconception of hard work, as well as a lack of the necessary explanatory knowledge in the agricultural study field. New students’ academic adjustment appeared to be the most problematic factor. It appeared that new students were insufficiently prepared to make the adjustment, and in fact, less prepared for this step than was generally the case in the past. Ineffective social integration was the result of too little student participation in social activities or the absence of adequate opportunities for social activities at agricultural training institutions. Unbalanced and unhealthy social activities were often the major factors that contributed to student dropout. Furthermore, the study demonstrated that non-academic factors such as inadequate accommodation or financial problems were not significant causative factors for student dropout, but rather non-academic factors such as unbalanced or unhealthy social activities and poor time management. After the probable causes for student dropout had been established, a theoretical framework was created that could offer possible explanation for the student dropout rates at agricultural training institutions. The framework was created to establish student dropout from a longitudinal perspective, and not only to explain the phenomenon as a result of what had occurred during the time that the student was at the institution. The framework was therefore designed to explain student dropout against the background of the student, together with various factors that were related to students or the institution and which were responsible for inadequate integration. From this framework it was possible to develop individual models for specific agricultural training institutions or for one specific institution in respect of the dropout phenomenon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".