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Record W3022153637 · doi:10.5206/eei.v30i1.10914

Enhancing Classroom-Based Communication Instruction for Students with Signifificant Disabilities and Limited Language

2020· article· en· W3022153637 on OpenAlexvenueno aff
Lori Geist, Karen A. Erickson, Claire W. Greer, Penelope Hatch

Bibliographic record

VenueExceptionality Education International · 2020
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
FundersU.S. Department of Education
KeywordsAugmentative and alternative communicationVocabularySign languageSign systemPsychologyMathematics educationManual communicationMeaning (existential)Symbolic communicationTeaching methodComputer sciencePedagogyMultimediaCommunicationLinguistics

Abstract

fetched live from OpenAlex

Many students with significant disabilities have complex communication needs and are not yet able to express themselves using speech, sign language, or other symbolic forms. These students rely on nonsymbolic forms of communication like facial expressions, body movements, and vocalizations. They benefit from responsive partners who interpret and honour these forms and teach symbolic alternatives. The purpose of this article is to describe ways in which classroom teachers and other classroom staff can be responsive partners using three targeted teaching practices: (a) attributing meaning and honouring early communication behaviours, (b) giving students personal access to aided augmentative and alternative communication (AAC) systems with a core vocabulary, and (c) using aided language input strategies to show students what is possible and how to use graphic symbols on aided AAC systems. These teaching practices are discussed using scenarios to illustrate how each can be integrated into typical academic and non-academic classroom activities.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.068
GPT teacher head0.456
Teacher spread0.388 · 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.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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