Language Choice Among Peers in Project-Based Learning: A Hong Kong Case Study of English Language Learners’ Plurilingual Practices in Out-of-Class Computer-Mediated Communication
Why this work is in the frame
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Bibliographic record
Abstract
Recently there has been considerable interest in the role of first language use in second/foreign language learning, especially where students share a common first language. However, most research has focused on in-class interaction between teachers and learners. Much less attention has been given to students’ out-of-class practices, for example, in collaborative project-based learning. To fill this gap, the article tracks the out-of-class activities of 16 students (four project groups) involved in project work on a course in English for science students at an English-medium university in Hong Kong. An analysis of students’ computer-mediated interactions (Facebook, WhatsApp and email) shows that these interactions are plurilingual, with students drawing on English, Chinese and mixed code to different extents as they go about their project work. Different languages are used strategically: whereas L2 is used more in the construction of the final project product, L1 is used more to promote group cohesion. The findings suggest that, in plurilingual contexts like Hong Kong, it is necessary to develop an English language pedagogy that acknowledges the need for the constructive but judicious use of translanguaging and plurilingual practices as students are engaged in L2-focused (e.g. EAP) project-based group work.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it