Facilitators and barriers to the implementation of learning through play for preschoolers in Kenya
Bibliographic record
Abstract
Abstract Access to equitable, quality, and inclusive early childhood education (ECE) has positive effects on school readiness, transition, and overall development and learning in all children. This paper seeks to explore barriers and facilitators to the implementation of learning through play (LtP) for preschoolers in Kenya with a view to enhance collaboration between parents and teachers. The current paper uses data from a broader study implemented in three counties in Kenya. This paper employs a qualitative approach. The study participants included parents (n = 119), teachers (n = 92), and policy makers (n = 06). The data were thematically triangulated and analyzed. Most parents recognized support from the school, the availability of play materials, and collaborations as critical facilitators to the implementation of LtP. Most teachers and policy makers noted that training and material development were key facilitators of implementing LtP. Potential barriers to the implementation of LtP included limited knowledge and skills in teachers to handle children with disabilities, limited awareness among parents, and lack of adapted play-based learning materials for children with disabilities. We emphasize that effective implementation of play-based learning may promote children’s learning and development outcomes. The success of this implementation calls for sustained collaboration between teachers and parents. The milestone inches beyond increasing learning outcomes to build a strong foundation for physical, mental, and socioemotional development in children. Further research may be conducted to explore the role of play-based learning in reducing social exclusions among children and caregivers with disabilities.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".