Perceptions of Teachers on the Ban of Corporal Punishment in Pre-Primary Institutions in Kenya
Bibliographic record
Abstract
The purpose of the study was to investigate perceptions of teachers on the ban of corporal punishment in pre-primaryinstitutions. The objectives of the study were to investigate teachers’ attitudes towards corporal punishment ban inpre-schools and to establish whether the level of education of teachers had an influence on the use of corporalpunishment. A descriptive survey design was used. Stratified sampling was used to select the pre-schools; simplerandom sampling was applied to select all the teachers in the pre-schools. Data was collected through questionnairesand analyzed using both quantitative and qualitative approaches. Major findings indicated that: 71% agreed thatreasonable corporal punishment is beneficial to the pre-school learners; 80% of the pre-school teachers used corporalpunishment to maintain order in the classroom; Teachers perceived negatively the outlawing of corporal punishment;the level of teachers’ education had no influence on the use of corporal punishment. The instances when corporalpunishment was used by teachers were non-academic. The results form a basis of re-thinking the initial teacherstraining curriculum and subsequent in-service training in regard to classroom disruptions and how best they could behandled. As changes occur in educational setting, courses for training of teachers in the initial course, inductioncourse or later in-service courses must reflect such changes and support and develop relevant skills in the staff uponwhom these changes will impinge. The teacher trainee ought to be exposed to other methods of behaviourmodification and these methods should have their own content and well researched.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".