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Record W3171906457 · doi:10.5539/elt.v14n6p125

Body Language as a Communicative Aid amongst Language Impaired Students: Managing Disabilities

2021· article· en· W3171906457 on OpenAlexvenueno aff
Nnenna Gertrude Ezeh, Ojel Clara Anidi, Basil Okwudili Nwokolo

Bibliographic record

VenueEnglish Language Teaching · 2021
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyLanguage assessmentBody languageCoping (psychology)Language acquisitionProcess (computing)Comprehension approachLanguage educationLinguisticsPedagogyMathematics educationCommunicationComputer science

Abstract

fetched live from OpenAlex

Language impairment is a condition of impaired ability in expressing ideas, information, needs and in understanding what others say. In the teaching and learning of English as a second language, this disability poses a lot of difficulties for impaired students as well as the teacher in the pedagogic process. Pathologies and other speech/language interventions have aided such students in coping with language learning; however, this study explores another dimension of aiding impaired students in an ESL situation: the use of body language. The study adopts a quantitative methodology in assessing the role of body language as a learning tool amongst language/speech impaired students. It was discovered that body language aids students to manage speech disabilities and to achieve effective communication; this helps in making the teaching and learning situation less cumbersome.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.350
Teacher spread0.335 · 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 designQualitative
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

Citations13
Published2021
Admission routes1
Has abstractyes

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Same venueEnglish Language TeachingSame topicHearing Impairment and CommunicationFrench-language works237,207