Teachers' experiences of a differentiated curriculum for children with autism spectrum disorder
Bibliographic record
Abstract
This study explored teachers' experiences in implementing a differentiated curriculum for children with severe intellectual disorders, including learners with autism spectrum disorder. The South African Differentiated Curriculum and Assessment Policy Statement (DCAPS) (2018) is a pilot study implemented by the Department of Basic Education (DBE) to adapt the existing Curriculum and Assessment Policy Statement (CAPS) to accommodate learners with high support needs to acquire skills and independence. This research followed a qualitative approach with a phenomenological multiple case study design. Eight teachers from four different schools in the Gauteng province participated. Data were collected through semi-structured interviews, document analysis, observations and field notes. In the interviews, teachers shared their thoughts, feelings and experiences about using the DCAPS (2018). The findings revealed the following major themes: (1) The teachers did not entirely understand the rationale behind the DCAPS (2018) curriculum for children with autism (2) teachers found the implementation of the differentiated curriculum difficult (3) teachers lacked sufficient training on the DCAPS (2018) curriculum. It was recommended that the Department of Basic Education (DBE) uses a professional developmental model that includes continuous monitoring and support. The study provides a stepping-stone for further research on the DCAPS (2018) curriculum for children with autism in South Africa.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".