Reconceptualising the Physical Sciences Curriculum and Assessment Policy Statement in a South African Context
Bibliographic record
Abstract
Post-apartheid South African curriculum reforms, from outcomes-based education (OBE) to the Curriculum and Assessment Policy Statement (CAPS), resulted in different challenges. Teachers, in particular those teaching Physical Sciences in the Further Education and Training (FET) phase from Grades 10-12, were expected to cope with changes and master Physical Sciences curriculum for the attainment of good results, but were unable to do so because they were missing an understanding of curriculum concepts. The success of any curriculum depends on ten fundamental and broad curriculum concepts: rationale, goals, activities, assessment, accessibility, resources, content, roles, environment, and time. However, empirical findings show that Grade 12 Physical Science teachers in South African schools still struggle to understand and contextualise curriculum concepts in order to redefine specific CAPS Physical Science concepts. Consequently, this conceptual study uses Van den Akker (2004) curriculum spider web concept framework in reconceptualising Grade 12 CAPS Physical Science concepts. This study argues that teaching without knowing specific subject curriculum concepts can lead to poor teacher performance and poor subject results, this study concludes by proposing a formal, non-formal and informal framework for CAPS Physical Science to resolve this.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".