Teacher Position in Spurring Value Based Education in Early Learning in Nairobi County, Kenya: Addressing Support of Values in School Environment
Bibliographic record
Abstract
Value Based Education (VBE) is an essential element that impacts moral, ethical, cultural, social and spiritual ideals necessary for holistic development of children. Providing an education on values at an early age ensures that children are directed by these ideologies throughout life. Research indicates that children who adopt values at an early age are confident, competent, independent, and exhibit harmonious social interactions throughout life time. Conversely, increase in juvenile delinquency, disrespect, drug abuse, school dropout, and conflicts in schools creates crisis in contemporary society. In such circumstances, VBE assumes a distinctive role to school deterioration process by strengthening morals and ethics within the society. The study explored influence of preschool teachers in spurring VBE among preschool children in Nairobi County focusing on; self control honesty, fairness, compassion and trust. A survey design was adopted with a target population of 36 public preschools. Purposeful sampling technique was then used to obtain data from 36 preschool teachers though use of a questionnaire. The study established that though teachers inculcate values to children both consciously and unconsciously, there is no planned value education program established on formal learning. The study recommends; regular training of teachers on use of VBE to deliberately foster intercultural understanding, social cohesion and inclusion, as well as need for value oriented programmes focusing on effective pedagogy.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 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) | 0.003 | 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".