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Record W4389308470 · doi:10.5430/wjel.v14n1p371

Functions of Code-switching in the Egyptian EFL Settings

2023· article· en· W4389308470 on OpenAlexvenueno aff
Ayman Khafaga, Mohammad Saeed Bekheet, Hanan Maneh Al-Johani, Iman El-Nabawi Abdel Wahed Shaalan

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersPrince Sattam bin Abdulaziz University
KeywordsCode-switchingClass (philosophy)Code (set theory)ArabicMathematics educationComputer scienceVariety (cybernetics)Process (computing)PsychologyLinguisticsPedagogyProgramming languageArtificial intelligence

Abstract

fetched live from OpenAlex

The main objective of this paper is to explore the alternation between languages, or what is recognized as the code-switching (CS) phenomenon among English language instructors in Egyptian universities. This is conducted by investigating the various purposes that might urge university instructors to code-switch between English and Arabic in their class interactions. This study, therefore, probes the extent to which code-switching is dexterously used in classroom discourse to communicate particular conversational and educational purposes pertinent to the teaching and learning process. Data are taken from 10 classes taught by five university teachers (two classes each) at the English Department, Cairo University. Data are collected through audio recordings of teachers' interactions in the class, and extracts from the participants' speeches are transliterated and analyzed. There are two overarching research questions in this study: first, do Egyptian university teachers of English code-switch? Second, what are the functions of teachers’ code-switching in classroom interaction? Findings indicate that there are instances of code-switching in the discourse of all five participants at varying levels. Findings also reveal a variety of conversational and educational purposes triggering code-switching by the participants. Despite the fact that the findings revealed in this paper are solely thought to be relevant to CS among English language instructors in Egyptian universities, they can be further applied to other classroom discourses and in other EFL settings.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.517
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.034
GPT teacher head0.399
Teacher spread0.365 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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