The Role of Special Education Teachers in Overcoming Developmental Disorders in Government Primary Schools in Northern West Bank
Bibliographic record
Abstract
This study aimed to identify the role of special education teachers in overcoming the growth disorders in public schools in Northern West Bank. The field descriptive method was used. To achieve this, a questionnaire was collected to collect data and information, which included (42) items, distributed into three areas. (Environmental, occupational, therapeutic) The validity of the tool was examined by presenting it to the academic supervisor and a group of arbitrators. The stability of the questionnaire was determined using the Cronbach's alpha equation, where the data were processed using the Statistical Package Program (SPSS). It was the results of the study that the role of special education teachers In overcoming growth disorders in public schools in Northern West Bank, it was found that there were no significant differences at the level of significance (α ≤ 0.05) in the role of special education teachers in overcoming growth disorders in public schools Nablus attributed to the variables of sex, educational qualification, years of experience, and after reviewing the results of the study came out several recommendations, the most important of which were: The need for the Ministry of Education to introduce modern technology in teaching students with growth disorders and to provide supporting technology to help them. The need to provide the appropriate educational tools and materials by the Ministry of Education to teach courses and integrated educational programs used with people with growth disorders considerate their different characteristics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".