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RECURSOS E FERRAMENTAS DE COMUNICAÇÃO AUMENTATIVA E ALTERNATIVA PARA PROMOVER A COMUNICAÇÃO DE ALUNOS COM NECESSIDADES EDUCACIONAIS ESPECIAIS

2025· article· pt· W4415969875 on OpenAlexaff
Clarice Rejane Lima Ferreira Tomaz, Anabela Cruz‐Santos

Bibliographic record

VenueREVISTA DIÁLOGOS E PERSPECTIVAS EM EDUCAÇÃO ESPECIAL · 2025
Typearticle
Languagept
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsAugmentative and alternative communicationAugmentativeInclusion (mineral)Disabled peopleSpecial education

Abstract

fetched live from OpenAlex

Given the need to use Augmentative and Alternative Communication in different contexts, it is important to know about studies that promote and discuss the implementation and development of these systems. The aim of this article is to contextualize part of the scenario of scientific knowledge production about the applications, purposes and development of Augmentative and Alternative Communication. It is an integrative review of articles published in journals indexed in different databases in Brazil and Portugal. Based on the application of previously established inclusion and exclusion criteria, 23 studies, including articles and dissertations, were selected to constitute the corpus of analysis. The results show that the studies analyzed recognize and consider the potential of Augmentative and Alternative Communication in communicative acts and social interactions between people with communication difficulties and their interlocutors. The research also showed the benefits in the teaching-learning process, considering the use of these systems as facilitators for effective communication in learning moments. Furthermore, there is a growing number of studies aimed at developing applications and technological devices to support communication. Therefore, it can be concluded that the studies support the understanding of Augmentative and Alternative Communication, as they present theoretical and practical knowledge, strategies, methodologies and resources. It should be noted that these systems are increasingly studied and have made progress in communication and inclusion of their users.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0050.003
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.076
GPT teacher head0.460
Teacher spread0.384 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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