Parental Age and Gender: How they Influence Knowledge and Perceptions of Inclusive Education for Children with Intellectual Disability
Bibliographic record
Abstract
Background: This study investigated how parental age and gender influence their knowledge and perspectives of inclusive education for their children with intellectual disabilities (ID). This study is essential as it provides valuable insights into how parental factors, such as age and gender, can shape their knowledge, perceptions, and attitudes toward inclusive education, which will likely impact the educational experiences and outcomes for children with intellectual disabilities. Methods: Employing a cross-sectional research design, the study surveyed 96 parents, consisting of 55 males (57.3%) and 41 females (42.7%). The participants were categorised by age: under 25 (n=20, 20.8%), 25-34 (n=24, 25.0%), 35-44 (n=28, 29.2%), and 45 and above (n=24, 25.0%). Data were collected using a structured questionnaire, demonstrating a reliability coefficient of 0.88 (Cronbach's alpha). The data analysis used Multivariate Analysis of Variance (MANOVA) to assess the main and interaction effects of parental age and gender on their knowledge regarding inclusive education. Results: Tests of Between-Subject Effects indicated a significant interaction between age and gender, F (3, 88) = 5.67, p < 0.01, revealing that older female parents (M = 4.10) had higher knowledge scores than older male parents (M = 3.60). Estimated marginal means supported these findings, explicitly showing significant differences between parents aged 25-34 and 45 and above (p < 0.05). These differences are evident in pairwise comparisons, particularly in the 35–44-year-old age cohort (M = 3.95). Conclusion: The results indicate that age and gender influence parental knowledge and perceptions of inclusive education. A targeted intervention considering these factors is crucial to enhancing supportive educational environments for children with ID.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".