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Record W2981127801 · doi:10.5539/ijel.v9n6p160

Professors’ and Undergraduate Students’ Perceptions and Attitudes Toward the Use of Code-Switching and Its Function in Academic Classrooms

2019· article· en· W2981127801 on OpenAlexvenueno aff
Raghad Y. Alkhudair

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitatorCode-switchingPerceptionMathematics educationCode (set theory)Computer scienceFunction (biology)Process (computing)PsychologySocial psychology

Abstract

fetched live from OpenAlex

This paper aims to determine the usefulness and functions of code-switching in the classroom when used by both lecturers and students. The study was conducted at a Saudi university campus and follows a quantitative approach using sets of questionnaires to collect the data. Then, the data were analyzed using SPSS (Statistical Package for the Social Sciences). Based on the analysis, the given study shows that professors and students consider code-switching from English into Arabic in the classroom as a beneficial instrument in enhancing the learning process. That is because it allows otherwise insurmountable problems for two-way communication in the L2 target language (English) to be overcome. Also, the findings of the current study reveal a range of positive attitudes toward using code-switching in two ways, Saudi-English immersion classrooms. Specifically, the majority of the professors use this technique in certain situations to achieve a better understanding by the students. In the same vein, students in this study show huge acceptance and prove how such a phenomenon has worked as a learning facilitator. It is hoped that the results of this study will be useful for professors and researchers investigating the importance of code-switching in the classroom.

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)0.001
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.020
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 head0.145
GPT teacher head0.471
Teacher spread0.327 · 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.

Study designObservational
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

Citations17
Published2019
Admission routes1
Has abstractyes

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