Conocimiento y uso de estrategias pedagógicas para estudiantes con TDAH en profesores y estudiantes de Pedagogía en Educación Media en Inglés en Chile
Bibliographic record
Abstract
ADHD is a neurodevelopmental disorder with a high prevalence, representing a challenge for the school system in general and for teachers in particular. The present study aims to evaluate the knowledge and use of pedagogical strategies for students with ADHD by graduate teachers and students of English Medium Education Pedagogy at a university in Chile. The Questionnaire of Knowledge of Pedagogical Strategies for Students with ADHD (CEPE-TDAH), based on the Canadian ADHD Practice Guidelines (CADDRA, 2018), was used. The sample consisted of 21 teachers and 44 students, revealing that teachers have greater knowledge and use of pedagogical strategies for working with students with ADHD than university student teachers (M=121.90 vs. M=113.20, p<.05). Overall results were observed, in both groups, unusually high with performances over 80% performance in knowledge and use of pedagogical strategies for students with ADHD, an issue that blurs the results. The reliability of the questionnaire was high (ω=.86) and the content validity was moderate (Aiken's V=0.53). Finally, the results suggest the need to improve ADHD training both at the teacher training stage and in professional practice. This work underscores the importance of providing effective pedagogical strategies to improve the performance and adaptation of students with ADHD in the English classroom.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".