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Record W2179097176 · doi:10.5539/ies.v8n12p56

The Relationship between WTC and Oral Proficiency Measurements in the Study Abroad Context

2015· article· en· W2179097176 on OpenAlexvenueno aff
Graham Robson

Bibliographic record

VenueInternational Education Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsFluencyLanguage proficiencyWillingness to communicatePsychologyContext (archaeology)Task (project management)Class (philosophy)Second-language acquisitionMathematics educationContext effectLinguisticsSocial psychologyComputer science

Abstract

fetched live from OpenAlex

Theories of second language acquisition such as the Interaction Hypothesis (Long, 1996) and Pushed Output Hypothesis (Swain, 1995) emphasize that learners must actually communicate in order to bring about the conditions for language acquisition. Learners who are more willing to communicate may create more opportunities for interaction, and thereby possibly improve their spoken proficiency. In L2 research fluency, accuracy and complexity have been used to extensively measure spoken output. This study uses qualitative and quantitative methods to investigate a largely under-researched area: whether there is a relation between fluency, accuracy and complexity, task engagement, and measures of willingness to communicate and actual learner communication and how these change for a group of 23 high-proficiency mainly Asian L2 English learners on a nine-week academic preparation course at a university in England.

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)0.002
metaresearch head score (Gemma)0.018
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.517
GPT teacher head0.476
Teacher spread0.041 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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