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Record W2345398193 · doi:10.5539/elt.v9n6p61

A Study of Interactions among Ambiguity Tolerance, Classroom Work Styles, and English Proficiency

2016· article· en· W2345398193 on OpenAlexvenueno aff
Hui-Hua Chiang

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAmbiguity toleranceAmbiguityPsychologyMathematics educationEnglish languageContrast (vision)Language proficiencyPopulationTOEICEnglish as a foreign languageSignificant differenceLinguisticsMedicineMathematicsComputer scienceStatistics

Abstract

fetched live from OpenAlex

<p>This article presents a preliminary investigation of the inter-relationships between English learners’ tolerance for ambiguity, their classroom work styles, and their level of English proficiency. The study population comprised 46 English as a foreign language (EFL) students attending a technical college in Taiwan. The findings indicated that a large percentage of these students had moderate to high levels of tolerance for ambiguity. In contrast to the findings of previous studies, our results showed no significant relationship between ambiguity tolerance and classroom work styles. The relationship between ambiguity tolerance and English proficiency in terms of the Test of English for International Communication (TOEIC) scores was almost statistically significant. However, tolerance for ambiguity and classroom work styles showed a statistically significant association with English proficiency. Recommended extensions of the study are discussed, and general directions for future research are suggested. Teaching implementations are also proposed.<strong></strong></p>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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 teacher head, 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

Citations20
Published2016
Admission routes1
Has abstractyes

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