<i>Who needs tildes anyways?</i> : a decolonial analysis of student engagement in translanguaging practices and pedagogies
Bibliographic record
Abstract
Employing translanguaging as a decolonial tool, this paper examines students’ translanguaging practices and their engagement with or resistance to translanguaging pedagogies. Specifically, this paper examines students’ translanguaging practices at Colegio Colombiano (CC), an international bilingual school in Colombia, and how students respond to the introduction of translanguaging pedagogies in their English classes. The guiding research question was: How do students engage in and make sense of translanguaging practices and pedagogies? Using qualitative data from classroom observations and focus group interviews, thematic analysis revealed elementary students were largely receptive to translanguaging pedagogies, while middle and high school students often resisted them despite engaging in translanguaging on their own terms. While older students indicated translanguaging pedagogies placed an unnecessary focus on their academic Spanish skills, a closer analysis revealed students’ complex resistance to and internalization of colonialist language ideologies and practices. This study provides a decolonial analysis of students’ engagement in translanguaging, highlighting the complexities of older students’ experiences. The article concludes with implications for a nuanced understanding and enactment of translanguaging, calling for international schools to actively challenge colonialist ideologies, make space for diverse linguistic identities and practices, and consider contextualizing, rather than borrowing, translanguaging pedagogies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".