Current Disciplinary Practices by Primary School Teachers in Eswatini: Implications for School Counselling
Bibliographic record
Abstract
This study explored current disciplinary practices by primary school teachers in Eswatini. A missed method design was employed using 48 primary teachers in the Hhohho region in the Kingdom of Eswatini. Instruments used were questionnaires and interviews. Data was collected and analyzed both quantitative and qualitatively. For analyzing data for questionnaires and observation, descriptive statistics such as frequencies and percentages were used and for analyzing data for interviews, thematic analysis was used. The findings of this study indicated that the participants are using guidance and counselling to discipline student as disciplinary measure. The study established that some disciplinary practises are not effective to curb students’ misbehaviour in schools such as corporal punishment and suspension. Conclusions arrived at indicate that public primary schools have adopted the use of guidance and counselling services. Few disciplinary practices were also found to be detrimental to academic performance. Therefore, this study suggested that guidance and counselling training should be given to all teachers. This therefore necessitates further investigation on the use of disciplinary practises and their impact towards the learner behaviour in all the four regions of Eswatini, since this study focuses in one region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".