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Record W2098633133 · doi:10.5539/elt.v4n1p26

The Relationship between Listening Strategies Used by Iranian EFL Freshman University Students and Their Listening Proficiency Levels

2011· article· en· W2098633133 on OpenAlexvenueno aff
Farinaz Shirani Bidabadi, Hamidah Yamat

Bibliographic record

VenueEnglish Language Teaching · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyMathematics educationCognitionListening comprehensionLanguage proficiencyDescriptive statisticsTest (biology)Communication

Abstract

fetched live from OpenAlex

The purpose of the current study was to identify Iranian EFL freshman university students’ listening proficiency levels and the listening strategies they employed to investigate the relationship between these two variables. A total of 92 freshmen were involved in this study. The Oxford Placement Test was employed to identify the learners’ listening proficiency levels and a Listening Strategy Questionnaire was used to identify the strategies they employed in listening. The descriptive analysis of the listening strategy questionnaire revealed that Iranian EFL freshman university students at advanced, intermediate, and lower-intermediate levels employed meta-cognitive strategies more frequently and actively; followed by cognitive and socio-affective listening strategies. The Pearson Correlation analysis also indicated that there was a significant positive correlation between the listening strategies employed by advanced, intermediate, and lower-intermediate freshmen and their listening proficiency levels at p<0.01 and p<0.05 levels respectively.

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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.062
GPT teacher head0.274
Teacher spread0.212 · 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

Citations77
Published2011
Admission routes1
Has abstractyes

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