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Record W2734587644 · doi:10.5539/ijel.v7n4p166

A Study of Probable Reasons for Saudi Learners’ Weakness in Listening Comprehension

2017· article· en· W2734587644 on OpenAlexvenueno aff
Sultan Samah A. Almjlad

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsListening comprehensionSignificant differenceActive listeningPsychologyComprehensionMathematics educationAggressionMedical educationDevelopmental psychologyLinguisticsMedicineMathematicsCommunicationStatistics

Abstract

fetched live from OpenAlex

This study investigates the listening comprehension problems of Saudi students. Forty Saudi postgraduate students from both genders (24 males and 16 females) participated in the study and all participants were postgraduate students at the University of Essex in the UK. The questionnaire was the only instrument used to collect data. The main findings of the study discovered were related to listeners first. Secondly, the study showed a significant difference between the academic lectures or seminars in five problems related to both listener and text, while thirdly the study showed a non-significant difference between the Saudi male and female students in terms of listening comprehension. Fourthly, the study discovered that the LC problems vary based on the learners’ academic levels as the LC problems get fewer when the academic level gets higher, confirming negative correlations between academic level and LC problems. After applying aggression analysis on some variables, the study also demonstrated that the length of studying English has a remarkable effect on the LC for Saudi students.

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)0.009
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.064
GPT teacher head0.330
Teacher spread0.266 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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