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Record W4408596312 · doi:10.5539/elt.v18n4p37

Navigating Identity: The Emotional Impact of English Medium Instruction on Saudi Undergraduate Students in a Rapidly Modernizing Society

2025· article· en· W4408596312 on OpenAlexvenueno aff
Khulod Aljehani

Bibliographic record

VenueEnglish Language Teaching · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyIdentity (music)Mathematics educationMedium of instructionPedagogyMedical education

Abstract

fetched live from OpenAlex

This study examines the socio-emotional impact of English Medium Instruction (EMI) on undergraduate students in Saudi Arabia and how various social and educational trends influence their attitudes, emotions, and perceptions of cultural identity. Using a qualitative research approach, the study employs focus group discussions and thematic analysis to explore students’ experiences. Three focus group sessions were conducted, each comprising five female students from different faculties and academic years, totaling 15 participants. Data collection involved semi-structured interviews, allowing for in-depth discussions on students’ challenges and coping mechanisms. Findings reveal that while students recognize the advantages of English proficiency for academic success, employment, and communication, they also experience anxiety, cultural tensions, and societal pressure related to English language use. Students report feeling more comfortable using English in informal settings, such as conversations with friends, but experience heightened stress in formal or professional environments. The results suggest that to alleviate the emotional and psychological burdens of EMI, educational institutions and policymakers should implement supportive strategies that address language anxiety and social isolation. The study highlights the need for inclusive learning environments that foster linguistic confidence and cultural integration while navigating the complexities of English as a dominant academic language in Saudi Arabia.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.028
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.012
GPT teacher head0.303
Teacher spread0.291 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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