Teacher Preparation in Zambia’s Expanded Core Curriculum: Challenges and Opportunities
Bibliographic record
Abstract
Well-prepared teachers are a determinant in the successful implementation of expanded core curriculum. Teachers can give learners skills according to the way they are prepared. Learners with visual impairments in special schools and students at tertiary level manifest deficits in critical skills required in academic success and transition in general. The nature of education of their teachers and challenges encountered during teacher preparation were not well established. The present study explored challenges faced in the preparation of teachers of learners with visual impairments in expanded core curriculum. Purposive sampling was used to select twenty-two teachers, two special education curriculum specialists and three Teacher educators. Open-ended questionnaires were used to collect data from teachers of learners with visual impairments and semi structured interviews were conducted with teacher educators and curriculum specialists. The findings indicated that teacher education/preparation in ECC was insufficient, and the institutions concentrated on braille literacy; and orientation and mobility. The remaining skills in ECC were ignored. Preparation incorporated few practical sessions and was highly theoretical. The major challenges among others were time constraints; insufficient resources in education; enrolments of student teachers; discrepancy between education and implementation; methodological issues. The opportunities were available to improve education were: employ more staff; embark on specialised education; advocacy and collaboration: offering continuous professional development for teachers. The study highlights the nature of preparation of teachers of learners with visual impairment. The teacher education institutions need to realign the curriculum through collaborative approach with other stakeholders so that teachers can effectively deliver skills to the learners.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".