Perceived usefulness of learning strategies by children with Tourette syndrome plus, their parents and their teachers
Bibliographic record
Abstract
Objective: Children with Tourette syndrome and other co-morbidities (abbreviated hereafter to TS+) experience significant learning difficulties. We wished to identify educational strategies that these students, their parents and teachers considered useful. Design: An ‘educational toolkit’ was compiled of 84 strategies identified by teachers of TS+ children. Setting: Children attending the TS+ clinic of a university hospital in Edmonton, Alberta. Method: The educational toolkit was administered to 30 randomly selected TS+ children attending the clinic, their teachers, and their parents. Results: 13 strategies were endorsed by ≥ 50% of the students, 53 by ≥ 50% of parents, and 42 by ≥ 50% of teachers. The 10 strategies students most strongly endorsed were: (1) computers; (2) calculators; (3) spell-checkers; (4) extra time in class; (5) less homework; (6) information from the teacher; (7) feedback on how to improve work; (8) printed assignments; (9) TS+ explained to their teacher; and (10) not being punished or suspended because of TS+ behaviours. The 10 strategies most frequently endorsed by parents were: (1) the student paying attention and being informed; (2) computers; (3) the teacher telling the whole class ‘listen carefully’ when discussing important ideas; (4) providing ideas about organizing work; (5) providing printed assignments; (6) telling students when they are being helpful; (7) encouraging students for good behaviour and signaling incorrect behaviour; (8) checking students understand each idea the teacher presents; (9) outside experts explaining TS+ to the teacher; and (10) exchanging notes with the teacher. The 10 items most strongly endorsed by teachers were: (1) providing information and direction; (2) feedback on how to improve work; (3) checking students wrote down homework assignments; (4) helping students start work assignments; (5) computers; (6) spell-checkers; (7) monitoring time and work; (8) extra time; (9) feedback about the student’s behaviour and advice if misbehaving; and (10) the teacher explaining to the class how students can help students with learning challenges. Conclusions: There is considerable agreement among parents and teachers about how to help children with TS+ with their schoolwork and behaviours.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".