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Record W2891178944 · doi:10.5539/elt.v11n10p38

Investigating Foreign Language Learning Anxiety Among Yemeni University EFL Learners: A Theoretical Framework Development

2018· article· en· W2891178944 on OpenAlexvenueno aff
Amr Abdullatif Yassin, Norizan Abdul Razak

Bibliographic record

VenueEnglish Language Teaching · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersUniversiti Kebangsaan Malaysia
KeywordsAnxietyPsychologyCronbach's alphaForeign language anxietyScale (ratio)Active listeningClinical psychologyForeign languageDevelopmental psychologyPsychometricsMathematics educationCommunicationPsychiatry

Abstract

fetched live from OpenAlex

This study aimed at investigating the level of foreign language anxiety experienced by Yemeni University EFL students. Although many scales have been developed to measure the level of anxiety, each scale investigates anxiety in one skill except Foreign Language Classroom Anxiety Scale (FLCAS) which investigates anxiety mainly in speaking and listening. The current study developed a new scale called Foreign Language Anxiety Scale (FLAS) which fused the three scales with modifications in order to investigate the level of anxiety in the four skills. This scale scored .807 in Cronbach’s Alpha Validity test. The participants are 155 Yemeni University students and the results of the analysis revealed that 13% of the students experienced high level of anxiety, 69% experienced moderate level of anxiety, and 18% experienced low level of anxiety. The general level of anxiety among Yemeni university EFL students is moderate as they score 138 out of 240.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.010
GPT teacher head0.229
Teacher spread0.218 · 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 designTheoretical or conceptual
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

Citations12
Published2018
Admission routes1
Has abstractyes

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