Storytelling in a Bilingual Classroom Through the Lens of Epistemic Diversity and Translanguaging
Bibliographic record
Abstract
ABSTRACT This case study explores the potential of storytelling as an academic activity, facilitated through translanguaging, to enhance epistemic diversity. By examining the intersection of epistemic diversity and translanguaging pedagogy, the study investigates how storytelling activities in a Turkish–English bilingual classroom impact young bilingual learners’ epistemic participation and linguistic flexibility in knowledge construction. The 18‐week study involved classroom observations and verbal recordings of 15 fourth‐grade Turkish–English bilingual students in Turkey. A translanguaging pedagogy framework, encompassing translanguaging stance, design, and shifts, was implemented to support students’ bilingualism. Thematic analysis reveals that Turkish–English bilingual learners dynamically select and alternate between their linguistic repertoires in Turkish and English, modifying noun, verb, and adjective phrases for meaning‐making during the storytelling, regardless of the story's theme. The students employ translanguaging patterns functionally for clarification and elaboration, as well as translating content words and simple sentence structures, fostering a form of epistemic cognitive diversity. The findings demonstrate how storytelling activities can serve as a platform for epistemic diversity by allowing students to access and express knowledge through their full linguistic repertoire. The study highlights that translanguaging practices during storytelling not only facilitate language learning but also promote diverse ways of knowing and understanding. The research contributes to the field by explicitly linking translanguaging pedagogy to epistemic diversity in the context of storytelling activities. It suggests that such activities can be strategically designed to foster both linguistic flexibility and diverse knowledge construction among young bilingual learners. The implications of this study extend beyond language acquisition, emphasizing the potential of translanguaging pedagogy to cultivate epistemic diversity in bilingual educational settings.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".