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Record W2787409185 · doi:10.5430/ijhe.v7n1p140

Letting the Cat out of the Bag: EFL College Students’ Attitudes towards Learning English Idioms

2018· article· en· W2787409185 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Higher Education · 2018
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsLikert scalePsychologyMathematics educationBattlePoint (geometry)English as a foreign languageForeign languageScale (ratio)PedagogyDevelopmental psychology

Abstract

fetched live from OpenAlex

Learning idioms is an uphill battle for many language learners. Thus, this quantitative study aims to shed light on English as Foreign Language (EFL) college students’ attitudes towards idiom learning. Specifically, the study is interested in revealing their attitudes towards (1) the importance of idiom learning, (2) the difficulties of idiom learning and (3) the learning strategies of idioms. Additionally, the study attempts to determine if there is an influence of age and/or year of study on the students’ attitudes towards learning English idioms. Participants were 218 female EFL college students at the College of Basic Education (CBE) in Kuwait. A five-point Likert-scale questionnaire was employed to obtain data for the study. Data analysis of the questionnaire uncovered the learners’ preferred strategies and sources of difficulties when learning idioms. Results showed that students had positive attitudes towards English idiom learning. Significant differences in the results were found when age was taken into account.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.019
GPT teacher head0.389
Teacher spread0.370 · 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