Affordances of Plurilingual Instruction in Higher Education: A Mixed Methods Study with a Quasi-experiment in an English Language Program
Bibliographic record
Abstract
Abstract While calls have been made for a multi/plural turn in Applied Linguistics, there remains a paucity of research investigating instruction that addresses the turn and its effects on student learning compared with monolingual one-language-only instruction. This study examines the effects of plurilingual instruction on students’ plurilingual and pluricultural competence (PPC) relative to monolingual English-only instruction. Moreover, it investigates potential additional affordances. Seven teachers in an English for Academic Purposes (EAP) program in a Canadian university taught two intact groups for four months: treatment (plurilingual instruction, n = 79) and comparison (monolingual instruction, n = 50) groups. Results from pre- and post-tests of the PPC scale show that students in the treatment group had higher PPC levels over time relative to students in the comparison group. Moreover, analyses of diaries and focus groups with students in the treatment group show that plurilingual instruction offers affordances such as cognition, empathy, and criticality. These results are significant as they suggest that plurilingual instruction may be more effective than monolingual instruction in the development of PPC and it offers several additional affordances.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".