Assessing Primary School Teachers’s Knowledge of Specific Learning Disabilities in the Kingdom of Saudi Arabia
Bibliographic record
Abstract
PURPOSE: Children with Learning disabilities require exceptional attention from family, their social circle and teachers. Because moral support and learning are initiated in the school environment by teachers (Padmavathi & Lalitha, 2009), the aim of this study is to evaluate primary school teachers’ knowledge about special learning disabilities in the Kingdom of Saudi Arabia. MATERIAL & METHOD: A sample of 902 primary private and puplic school teachers from 78 schools across different regions of Saudi Arabia was selected using a convenience sampling technique. Teachers’ knowledge about learning disabilities was surveyed electronically using a structured knowledge 40-item questionnaire on learning disabilities. A descriptive and quantitative approach was used to assess their knowledge. SPSS v21 was used to analyze the data. RESULTS: The study found that a majority of primary school teachers have average knowledge about specific learning disabilities. Consequently, teachers’ range of knowledge has statistically significant impact on their level of knowledge. The study correspondingly shows a significant relationship between levels of knowledge and socio-demographic variables, but no statistically significant difference in the knowledge level of male and female teachers regarding learning disabilities. CONCLUSION: Teachers do not have adequate knowledge regarding learning disabilities, and do not know what should be done when facing such issue. Teachers’ knowledge about learning disabilities is insuficient, because their academic training did not include any courses about it. As a consequence, education lawmakers should arrange appropriate teacher training or structured learning programs regarding learning disability concepts, assessment, diagnosis and identification for such teachers.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".