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Record W4401340541 · doi:10.14393/ufu.di.2022.5357

O ensino de química para surdos: produção de planos de aula especializado para turmas inclusivas

2018· dissertation· pt· W4401340541 on OpenAlexaff
Ronaldo Marques

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsBibliographical Society of Canada
Fundersnot available
KeywordsInterpreterPoint (geometry)PsychologyMathematics educationComputer scienceLinguisticsPedagogyPhilosophyMathematicsProgramming language

Abstract

fetched live from OpenAlex

The present work aims to propose the creation of Specialized Classroom Methods (SCM) for deaf students, so that it is possible to strengthen the bonds between teachers and interpreters and to provide students with a better understanding of the chemical content. The creation of the SCM’s showed that for the teaching of inclusive classes of deaf students it is necessary to denote aspects inherent to the deaf culture, such as more imagistic classes, more phenomena and even adaptations of scientific terms that will allow a better understanding of what is being studied. It is concluded that the main key for a better development of inclusive classes is the communication between teacherinterpreter, since the communication channel between these parts improves the teacher understands the function of the interpreter, and the interpreter knows the objective of the teacher. Within the proposed creation of model plans, to analyze the learning mode of deaf students, from the point of view of interpreters and teachers, aiming to understand the failures in learning mechanisms and propose, within the SCM, new structures to reduce the learning gap of deaf students and listeners.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.001

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 head0.081
GPT teacher head0.372
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; 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
Published2018
Admission routes1
Has abstractyes

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