Teaching Elementary-Aged Children on the Autism Spectrum: The Key Issues, Challenges and Successes Described by Specialist Teachers
Bibliographic record
Abstract
The most recent prevalence rates from the Public Health Agency of Canada’s National ASD Surveillance System (NASS) (PHAC, 2018) indicate that 1 in 66 children and youth (i.e., 15.2 per 1000) 5-17 years of age were diagnosed with ASD in 2015 across seven provinces and territories. The Ontario Ministry of Children and Youth Services (MCYS) states that there are an estimated 40,000 children and youth with ASD in the province (“Newsroom: Ontario Providing More Supports for Children with Autism,” 2016). Specifically, in the context of Ontario’s education system, and in light of the current study, there is a rapid increase of students with exceptionalities no longer being isolated to special education classrooms, as a result, general education teachers are increasingly teaching the autism spectrum disorder (ASD) student population (Wilczynski et al., 2011). A large number of studies determine that general education teachers do not support an inclusive model of teaching as they lack adequate training in teaching inclusively, as well, they voice concerns about their lack of confidence, feelings of low self-efficacy, and have expressed a shortage of continuing education opportunities (Finke, McNaughton & Drager, 2009; Lindsay et al., 2013; McCray & McHatton, 2011; Ross-Hill, 2009; Scruggs et al., 2007). This study aimed to fill in the gap by exploring the experiences of specialist teachers who have worked more extensively with students with ASD. \nSpecifically, this qualitative descriptive study describes effective strategies used by four specialist teachers that support the inclusion of students with ASD. In talking to specialist teachers about effective strategies they use, I hoped to gain an in-depth understanding of their attitudes and beliefs towards including students with ASD, and learn how teachers create a safe and accepting environment within their classrooms through the use of different tools, resources and practices. \nThe findings of this study suggest that it is important that educators who work with students with ASD be highly committed; in that, they are driven to find resources and tools, willing to adapt their classroom routine/instruction, and demonstrate resiliency when faced with challenges. Furthermore, the specialist teachers stressed the importance of tailoring instruction to suit the individualized functional needs of students, as opposed to a sole focus on curriculum and diagnosis. This study also suggests that a structured but flexible learning environment is fundamental to teaching inclusively (i.e., teaching content using multiple modes and in different settings based on student needs). Most importantly, this study provides an overview of a number of strategies deemed successful in supporting the inclusion of students with autism spectrum disorder and provides detailed descriptions and explanations of how and why each strategy is used in practice. This study provides useful information for individuals at all levels of education, from government policy makers to front-line teachers by making classroom-validated resources, practices and affective factors transparent and scalable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".