Teacher Mentorship and Support in Kenya: A Desktop Review
Bibliographic record
Abstract
Teacher mentorship and support programmes enable teachers to engage in ongoing professional learning and develop required competencies. This exploratory study was designed to provide baseline information on existing teacher mentorship and support programmes in Kenya. The study sought to provide background information towards the implementation of participatory action research on the strengthening in-service teacher training (SITT) project funded by the International Development and Research Centre (IDRC). The study adopted an integrative and holistic approach that involved a review of government policy documents, circulars and reports, articles published in refereed journals and grey material to enable map existing teacher mentorship and support programmes in Kenya. The study sought to; describe the theoretical background of teacher mentorship and to document existing in-service teacher mentorship and support programmes in Kenya. Various in-service teacher mentorship and support programmes exist in Kenya. However, the majority of the programmes were funded and implemented by non-governmental organisations. The existing mentorship programmes were uncoordinated and lacked a follow-up mechanism, thus making them less effective.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".