Bridging worlds with words: translanguaging and its impact on identity formation among Jordanian graduate students in Ontario
Bibliographic record
Abstract
Translanguaging, an approach to multilingualism, enables individuals to draw from their entire linguistic repertoires, challenging traditional language boundaries. This study explores how translanguaging practices influence identity formation, academic integration, and social adaptation among Jordanian graduate students in Ontario, Canada, where linguistic diversity and bilingualism present unique challenges and opportunities for cultural expression. A qualitative research design was used, involving semi-structured interviews with 10 Jordanian graduate students who identify as bilingual in Arabic and English. Data were collected through interviews conducted in both languages, ensuring comfort and authenticity in participants’ responses. Thematic analysis was applied to identify patterns in translanguaging practices and their perceived impacts on identity and academic experiences. Findings indicate that translanguaging facilitates identity expression, allowing students to bridge their Jordanian heritage with their new Canadian academic environment. Participants reported enhanced comprehension of academic material, improved confidence in class participation, and increased social cohesion through linguistic flexibility. However, they also highlighted challenges, including experiences of linguistic stereotyping and a lack of institutional support for multilingual practices. The study underscores translanguaging as a critical tool for identity negotiation, academic success, and social integration, advocating for educational policies that acknowledge and support its value in multicultural and multilingual settings. The implications highlight the need for inclusive language practices in higher education to foster belonging, respect for linguistic diversity, and academic achievement among international students.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".