Promoting the Social Inclusion of Students with Autism Spectrum Disorder via Mobile Technologies
Bibliographic record
Abstract
Autism Spectrum Disorder (ASD) is the most commonly diagnosed neurodevelopment disorder in Canada, and approximately 1 out of 66 children is identified with ASD in Canada. Children with autism demonstrate impairments in language, communication skills, and social interactions; hence, these children have difficulties with communicating and interacting socially with their peers, educators, and parents. One of the latest interventions is the use of mobile technologies in assisting children with ASD in developing their social, communication, language, and other educational skills required for their academic success. However, social inclusion of these students in the classroom is still challenging. Hence, there is a need to determine effective ways of integrating mobile technologies in the classroom in order to promote the social inclusion of students with ASD. Using case study research, this mixed method study explored how students with ASD are socially included in the learning activities using mobile technologies and the impact on educators and parents. Educators, other education professionals, and parents participated in surveys and one-on-one interviews to provide further insights about their experiences in meeting students’ communication, social, language, and educational needs via mobile technologies. Analysis of both quantitative and qualitative data resulted into four emerging themes: (a) a balanced learning model where social inclusion of students with ASD is supported through the balance between mobile technologies and personal interaction; (b) resources and supports such as open educational resources, funding to support mobile technologies, evidence-based knowledge on mobile technologies, and training for all stakeholders are necessary in creating a socially inclusive environment for students with ASD; (c) goal oriented and needs-based usage where mobile technologies are used for addressing the needs of students with ASD and for achieving a particular goal or purpose in education; and (d) a team oriented approach that involves collaboration among students, parents, school administrators, educators, other education professionals, and various stakeholders in promoting the social inclusion via mobile technologies. The findings from this research study indicated various aspects (promoters) that are important in promoting the social inclusion of students with ASD via mobile technologies. Through these promoters, effective levels of social inclusion can be achieved where students’ communication, social, language, and educational needs are addressed sufficiently.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".