Understanding the Educational Experiences of Autistic Learners and Their Families in Ontario, Canada During COVID-19-Related School Closures
Bibliographic record
Abstract
The focus of this study was the educational experiences of autistic learners and their families during COVID-19-related school closures in Ontario, Canada. The problem addressed by the study was the existing gap in knowledge and understanding related to the unique educational experiences of autistic learners and their families in Ontario during COVID-19-related school closures which will prevent policy makers, educators, and parents from better supporting autistic learners’ educational needs in the future. The guiding theoretical framework of this study was Bronfenbrenner's Ecological Systems Theory (Bronfenbrenner, 1977). Nine parents whose children were enrolled in an Ontario public or Catholic school and who were 8-13 years old at the start of the pandemic were interviewed for this study. Braun and Clarke’s (2006) six-phase framework for Thematic Analysis was used to code and analyze the data using NVivo 12. Nine themes emerged from the data. The first two themes demonstrated that autistic learners’ and their families’ educational experiences during COVID-19-related school closures varied widely, from being positive and beneficial to being very challenging and detrimental, to the child’s learning and their social and communication skills. The third and fourth themes highlighted the varied ways in which autistic learners responded to school closures and their subsequent impacts on their daily routines. Themes 5-8 highlighted how access to educational supports (i.e. Educational Assistants), assistive technologies, hands-on support from parents and grandparents, and varied forms of privilege (i.e. parents’ ability to work flex hours and from home, private learning spaces within the household, limited number of siblings) were important factors that influenced a child’s educational experience while learning from home during school closures. The study’s last theme found that the COVID-19 educational experience has elicited within parents a desire to remain more actively involved in their child’s education than they were prior to the pandemic. The study concluded with ten considerations for policy makers, educators and parents to adopt both during and beyond school closures to help better support autistic learners unique learning needs, and shared four recommendations for future research based on gaps identified within existing research on the topic and emerging from this study’s findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".