Educational Inclusion of Children with Down Syndrome in Kuwait: Challenges from Kindergarten Teachers’ Perspectives
Bibliographic record
Abstract
Understanding the challenges of inclusive education is essential for evaluating its effectiveness. By identifying these obstacles, stakeholders, policymakers, and educators can systematically address the issues. This study investigates the barriers to including children with Down syndrome in kindergartens in Kuwait, focusing on teachers’ perspectives. Using a descriptive survey method, the researcher designed a questionnaire with two sections: the first covered demographic variables, and the second consisted of 32 items addressing the study’s themes. The questionnaire was distributed to a sample of 90 kindergarten teachers in Kuwait. Data on the challenges hindering the inclusion of children with Down syndrome, as perceived by the teachers, were collected and analyzed using appropriate statistical methods.The findings revealed that administrative barriers were the most significant, with a mean score of 3.86 and a standard deviation of 0.70. The lack of clear policies supporting inclusion was identified as the primary barrier from the teachers’ perspective. Furthermore, concerns were raised about inadequate infrastructure, such as the absence of safe spaces and poor building design. Regarding family-related barriers, the results indicated that families also posed challenges to implementing inclusion for children with Down syndrome in kindergartens.The study recommended implementing awareness programs and workshops for teachers, parents, and non-disabled students to improve understanding of the needs of children with Down syndrome in inclusive kindergarten settings.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".