A Retrospective Analysis of Technology Use Patterns of Students with Autism over a Five-Year Period
Bibliographic record
Abstract
Since 1993, students with autism in British Columbia schools have received technology supports through a provincial government initiative. This retrospective, exploratory study involved a file review of students with autism who participated in this initiative over a five-year period. The following questions were addressed. Who were the students with autism to whom technology was provided? What type(s) of technology did they receive? What were the profiles of students who received specific types of technology? For which educational goal areas was technology used? How successful was it? Results suggested that the majority of students received technology for educational participation while a smaller number received voice output communication aids; some students received both types of technology. The primary goals for which technology was used were related to writing, expressive communication, and social interaction. When numerical “success scores” were assigned to teachers' annual reports of the outcomes of technology use, 60% of the students were assigned scores suggesting successful or very successful use, and only 12% were scored as having little or no success. Success scores did not appear to be related to students' cognitive ability, but students who received technology at a young age appeared to experience more success than those who received it as adolescents. The preliminary results are discussed in terms of the potential for positive outcomes of technology use by students with autism and the need for additional research in this area.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".