MétaCan
Menu
← Back to cohort
Record W4389820036 · doi:10.5430/wjel.v14n1p461

Anxiety Experienced by Students with Learning Disability in English Speaking Classroom

2023· article· en· W4389820036 on OpenAlexvenueno aff
PA Kayal Vizhi, Maya Rathnasabapathy

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyPronunciationPsychologyMistakeLearning disabilityFluencyClass (philosophy)VocabularyGrammarMathematics educationDevelopmental psychologyLinguisticsComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

This study sought to explore the anxiety experienced by students with learning disability in English speaking classroom. For this study 33 students with English language learning disability were selected from Chennai special school. Both qualitative and quantitative analysis methods were used to assess the level of anxiety experienced by learners with learning disability in English class. The study’s results show that learners with English language learning disability experienced an extreme level of anxiety. In addition, the findings show that there is no significant difference between male and female learners with language learning disability in terms of speaking anxiety. Besides, the findings show that there is no significant difference between urban and rural students with language learning disability in terms of speaking anxiety. Furthermore, the findings show that fear of making mistake, lack of confidence, lack of vocabulary, lack of grammar knowledge, lack of fluency and incorrect pronunciation are the major sources of speaking anxiety for learners with language learning disability. The study addresses the sources and level of anxiety that students with learning disability have while communicating in English classroom.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
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 head0.012
GPT teacher head0.267
Teacher spread0.255 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of English Language→Same topicEFL/ESL Teaching and Learning→French-language works237,207→