Translanguaging in the Saudi EMI Classroom: When University Instructors Talk
Bibliographic record
Abstract
The past few decades have witnessed a growing interest in using English as a Medium of Instruction (EMI), especially in higher education. Although the English language has rapidly shifted from being taught as a foreign language to becoming a medium of instruction, empirical research in this area is still limited in the context of the Middle East and North Africa (MENA), especially in Saudi Arabia. Therefore, the present case study explores translanguaging in the EMI classroom. The study used semi-structured interviews to investigate teachers’ perceptions and practices regarding translanguaging, the rationale behind such practices, and the pedagogical effect of implementing translanguaging practices. The data was collected from five university professors majoring in medicine, physics, electrical engineering, and computer science using purposive sampling. It was analyzed using thematic qualitative analysis. The findings show that the participants generally have a positive attitude toward translanguaging, as it was triggered by students’ limited language proficiency and the contextual and psychological situation of the students in the classroom. The results also indicate that it facilitates content comprehension and aids in raising student engagement and reducing language anxiety. Consequently, adopting translanguaging strategies in EMI classrooms with caution is recommended to provide a wealth of advantages and chances for students’ linguistic growth, engagement, and academic success. Professional development programs and assessments of students’ needs are necessary to ensure the prudent use of translanguaging in class and improve EMI classrooms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".