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Record W92538349 · doi:10.1177/016264340001500301

A Retrospective Analysis of Technology Use Patterns of Students with Autism over a Five-Year Period

2000· article· en· W92538349 on OpenAlexaff
Pat Mirenda, Diana Wilk, Paul E. Carson

Bibliographic record

VenueJournal of Special Education Technology · 2000
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAutismPsychologyPeriod (music)Special educationEducational technologyGovernment (linguistics)Medical educationDevelopmental psychologyMathematics educationMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.011
GPT teacher head0.315
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2000
Admission routes1
Has abstractyes

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