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Record W4413412584 · doi:10.3389/feduc.2025.1614353

Foreign language anxiety in EFL classrooms: teachers' perceptions, challenges, and strategies for mitigation

2025· article· en· W4413412584 on OpenAlexaff
Shaden Samir Attia, Muath Algazo

Bibliographic record

VenueFrontiers in Education · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsFanshawe College
Fundersnot available
KeywordsAnxietyPerceptionEnglish as a foreign languageForeign languagePsychologyForeign language anxietyMathematics educationComputer sciencePedagogyMedical educationMedicine

Abstract

fetched live from OpenAlex

This study investigates Foreign Language Anxiety (FLA) in English as a foreign language (EFL) classrooms in Egyptian higher education. The study was conducted at multiple universities in Egypt, where English is widely taught and learned as a foreign language. Data was collected through a questionnaire completed by 49 EFL instructors, supplemented by five one-to-one semi-structured interviews with participants from the questionnaire. The results demonstrate that EFL teachers generally acknowledge and frequently observe FLA among students, particularly during speaking activities. Specific sub-skills such as summarizing and presenting were identified as anxiety-inducing. Although some instructors consider FLA motivating, others view it as detrimental to student progress. Instructors also suggest creating supportive environments where mistakes are valued as part of the learning process to mitigate FLA. Interestingly, it was found that instructors themselves may experience FLA, particularly when speaking with native speakers or teaching in a second language (L2). Strategies suggested by instructors to alleviate FLA include group discussions, role plays, individual activities with preparation, and peer support. Overall, instructors' attitudes, rapport, and feedback play a crucial role in managing FLA levels in the classroom. This study contributes to raising awareness among stakeholders toward FLA in Egypt and the broader EFL context.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.271
Teacher spread0.259 · 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 teacher head, 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

Citations8
Published2025
Admission routes1
Has abstractyes

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