Perspectives of Individuals Engaged in Inclusive Teaching Activities for Children with Disabilities in Primary Schools
Bibliographic record
Abstract
This research aims to examine the current state of inclusive teaching for children with disabilities in primary schools within the South-Central region, Vietnam. A survey involving administrators, teachers, and parents was conducted across 30 primary schools in Da Nang City, Phu Yen Province, and Ninh Thuan Province. The study investigates participants’ perceptions of inclusive teaching activities, the realization of inclusive teaching objectives, content alignment, teaching methods, and assessment practices. Survey data from 390 participants was analyzed to extract insights and patterns. The data collection took from December 2020 to August 2021. The study explored perceptions of inclusive teaching importance, revealing that 7.95% found it “very important”, 8.97% deemed it “important”, 13.85% considered it “less important”, and 69.23% found it “not important”. The assessment of correctness yielded mean scores ranging from 1.65 to 3.50. The achievement of inclusive teaching objectives scored between 3.37 and 3.47. Integrating inclusive teaching content received mean scores from 3.35 to 3.50. Various teaching forms scored between 1.60 and 2.36, indicating potential improvements. Inclusive teaching methods scored between 1.76 and 3.40. Evaluation and assessment mean scores ranged from 1.70 to 2.22. This research contributes to the ongoing dialogue on inclusive education, offering a comprehensive understanding of the challenges and opportunities in providing effective and inclusive learning experiences for children with disabilities in the South-Central region, Vietnam.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".