Designing a modern language course for culturally and linguistically diverse students
Bibliographic record
Abstract
Cultivating learners’ multimodal communication skills and their intercultural awareness is necessary for effective collaboration. With this aim, a translanguaging dual language (TDL) course was developed at a Japanese multilingual university drawing on the pedagogy of multiliteracies (PoM) and translanguaging. The research questions this study addressed were: (1) What kinds of teaching and learning activities can be provided to allow students to negotiate and co-create knowledge? (2) How do students in a tertiary TDL course engage with the PoM? In the course, role-play videos were made by students to demonstrate approaches to communication with their classmates from various backgrounds. A multimodal textual analysis of the video data was conducted. The findings suggest that the course fostered students’ capability of engaging and negotiating locally situated communication strategies using various semiotic resources including translanguaging. This article also suggests pedagogical implications for student-oriented classrooms that allow space for students’ negotiation and co-construction of knowledge.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".