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Record W4391187908 · doi:10.5539/elt.v17n2p1

Triggers for Foreign Language Speaking Anxiety: Perceptions of Saudi EFL College Students

2024· article· en· W4391187908 on OpenAlexvenueno aff
Mohammed Ali H Faqihi

Bibliographic record

VenueEnglish Language Teaching · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAnxietyPerceptionForeign language anxietyEnglish as a foreign languageForeign languageMathematics educationLinguisticsPedagogy

Abstract

fetched live from OpenAlex

The primary aim of the present study is to investigate foreign language speaking anxiety (FLSA) levels and the factors triggering language speaking anxiety among Saudi EFL college learners. The study adopted a mixed-method approach to meet the research objectives. A Foreign Language Classroom Anxiety Scale (FLCAS) questionnaire was employed. The sample of the study consisted of 39 male Saudi students at Al-Quaiyah College of Technology. Subsequently, eight of the most anxious students were identified based on the questionnaire results. The results revealed that the participants experienced a moderate level of FLSA in their English class. The participants reported several major causes of their speaking anxiety in the language class, such as a lack of preparation and vocabulary knowledge, forced participation, and other teacher-related factors. The study recommends that teachers should inform their students about what will be discussed in advance to help them become more prepared and less anxious. Moreover, teachers should encourage and motivate students to participate in oral activities instead of forcing them.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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 designQualitative
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

Citations3
Published2024
Admission routes1
Has abstractyes

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