Teachers’ perspectives on the student-teacher relationship quality in female students with autism spectrum disorder
Bibliographic record
Abstract
While the student-teacher relationship is highly associated with students' and teachers’ success and development, students with autism spectrum disorder (ASD) tend to have relationships characterized by higher levels of conflict and lower levels of closeness. Much of the research, however, has used primarily male samples when investigating ASD. This poses a risk to the generalizability of the findings to the female experience as studies have found that females with ASD tend to present different symptoms than males with ASD. The current study utilized a survey research design to examine Canadian elementary school teachers’ perceptions of the quality of their student-teacher relationship with their female students with ASD and its possible associations with teacher and student characteristics. Teachers in this study reported having low- quality relationships with their female students with ASD with high levels of conflict and dependency, and low levels of closeness. Results also indicate a negative correlation between teachers’ experience teaching and the student-teacher relationship quality. Neither previous exposure to individuals with ASD nor previous training in ASD were found to be associated with the student-teacher relationship quality. However, having specific training involving sex-related differences in ASD was associated with a more positive student-teacher relationship quality. Teachers’ confidence and knowledge in working with females with ASD were also associated with the student-teacher relationship quality. Additionally, student-related characteristics (e.g., social and communication skills symptom severity, internalizing and externalizing problems) were negatively correlated with the student-teacher relationship quality. Implications for research and practice, as well as future directions, are presented.
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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 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".