Implementing the updated Early Childhood Development curriculum in Zimbabwean primary schools: Social Validity Based on Practitioners’ Views
Bibliographic record
Abstract
This article analysed the level of social validity on implementing the updated Early Childhood Development (ECD) curriculum in Epworth, Mabvuku, Tafara (EPMAFARA) District in Harare, Zimbabwe. To address the ever-changing world economy, Zimbabwe introduced an updated curriculum in all its primary schools, in 2017. The updated curriculum provides a framework for the knowledge that help young people to develop a sense of independence and self-reliance. A qualitative method was employed to explore curriculum implementation in Zimbabwean primary schools. Data were collected from a purposively selected sample of two District Schools Inspectors, four School Heads/ Teachers in Charge and eight ECD teachers. The data were analysed using the NVivo software. The researchers discovered that as well as exposing some gaps in the implementation practice, the study revealed some advantages namely, competence-based component, child centred methods, skills-based approaches, change and nurturing of various children’s talents among others. The disadvantages encountered comprised lack of financial and human resources and school basic infrastructures, excessive workload for teachers, lack of Information, Communication and Technology skills and high- teacher: pupil ratio. The qualitative research method used was one major limitation since it was time consuming and, labour intensive. The researchers' initial sample was further affected by COVID-19's onset in the country in March 2020, when the World Health Organization (WHO) advised lockdown limitations, causing schools to close abruptly. The paper’s findings underscored the significance of planning for change in ECD educational programs in terms of teachers’ preparedness and stakeholders’ resourcefulness. These findings imply that teachers should be trained to become innovative and creative in curriculum implementation. Stakeholders are recommended to support teachers and schools with prerequisite resources.
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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 | 0.078 | 0.168 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".