Saudi Arabian Pre-Service Special Education Teachers Knowledge of Attention-Deficit/Hyperactivity Disorder (ADHD)
Bibliographic record
Abstract
The current study aims at detecting the level of knowledge held by special education student teachers at Umm Al-Qura University with regard to Attention-Deficit/Hyperactivity Disorder (ADHD), and comparing their level of knowledge of (ADHD) according to variables: Gender (male or female), track or specialty (special education ,mental disability, learning disabilities, hearing disability, behavioral disorders and Behavioral Disorders and Autism), school year or university level (first year, second year, third year, and fourth year). The sample of the study consists of (682) students who were selected randomly from the Department of Special Education at Umm Al-Qura University in Makkah in the Kingdom of Saudi Arabia for the academic year (1437H-1438H), and SPSS was applied for data analysis. The results showed that Saudi Arabian Pre-Service Special Education Teachers’ overall knowledge is high (64.2%). The correct rate of knowledge of ADHD was (93.0 %) and (86.8) (‘high’), respectively. As for the sex differences were in favor of females, as for year and track or specialty variables, Pairwise Multiple Comparisons Post Hoc Test using LSD method. Implications of the study results are discussed, and recommendations are presented.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".