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Record W2336425866 · doi:10.5539/elt.v9n5p154

The Impact of Listening Strategy Training on the Meta-Cognitive Listening Strategies Awareness of Different Learner Types

2016· article· en· W2336425866 on OpenAlexvenueno aff
Fatemeh Zarrabi

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyMetacognitionTest (biology)Phonological awarenessCognitionMathematics educationCognitive psychologyPedagogyLiteracyCommunication

Abstract

fetched live from OpenAlex

The present study investigated the effectiveness of listening strategy instruction on the metacognitive listening strategies awareness of different EFL learner types (LTs). To achieve this goal, 150 EFL students took part in the study and were taught based on a guided lesson plan regarding listening strategies and a pre-test/post-test design was applied. The degree of change occurring as a result of intervention was measured through one way ANOVA test. The results indicated that there was a significant improvement after the onset of the instruction, and that the intervention was effective. Although there were some differences between the four learner types (visual learners, auditory learners, kinaesthetic learners, and tactile learners) on the post test, the auditory learner type had the most significant improvement in metacognitive awareness of listening strategies (MALS). The finding of this quantitative research study led us to conclude that learners make noticeable progress in MALS via listening strategy instruction and that the level of improvement varies across the LTs with the auditory group improving most significantly.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.311
Teacher spread0.250 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

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