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Record W1535331030 · doi:10.5206/eei.v24i1.7709

Professional Development Needs for Educators Working with Children with Autism Spectrum Disorders in Inclusive School Environments

2014· article· en· W1535331030 on OpenAlexafffundvenue
Penny Corkum, Susan E. Bryson, Isabel M. Smith, Cynthia Giffin, Kym Hume, Ann Power

Bibliographic record

VenueExceptionality Education International · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsDalhousie University
FundersNova Scotia Health Research Foundation
KeywordsAutismProfessional developmentSpecial needsInclusion (mineral)PsychologySpecial educationMedical educationFaculty developmentFocus groupAutism spectrum disorderMainstreamingPedagogyMedicineDevelopmental psychologySociology

Abstract

fetched live from OpenAlex

The primary objective of this mixed methods study was to identify educators’ professional development needs to determine how best to support them in providing quality programming for children with Autism Spectrum Disorders (ASD) within an inclusive educational system. Information was collected through focus groups with key school board informants (n = 33) and a survey of educators (n = 225). The results indicate that educators have found it difficult to meet the wide-ranging and varying needs of children with ASD within a strictly defined model of inclusive education. Educators consistently emphasized the need for multileveled and multipronged professional development that is accessible in a timely fashion and available as needs arise. The need for educational programs that work for children with ASD being taught within inclusive education settings is highlighted.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.307
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations37
Published2014
Admission routes3
Has abstractyes

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