Empowering Teachers to become Change Agents through the Science Education In-Service Teacher Training Project in Zimbabwe
Bibliographic record
Abstract
This paper presents findings from a study of three Zimbabwean science teachers who participated in the Science Education In-service Teacher Training (SEITT) program. At the turn of the century, the SEITT program was designed to develop science and mathematics teachers into expert masters and resource teachers for Zimbabwe’s ten school districts. The study investigated the successes and challenges faced by the three teachers who were in the process of reforming their pedagogical practices as well as writing and using contextualized science curriculum materials to teach secondary science. Data were collected through telephone interviews. The three teachers reported that the SEITT program helped them to transform their practice as well as that of their peers. They also reported that changing their teaching methods motivated learners to actively participate and this change also resulted in improved teacher efficacy. The paper discusses implications for improving science teaching and suggestions for contextualizing the science curriculum in developing countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".