The Common European Framework of Reference (CEFR) in French immersion teacher education
Bibliographic record
Abstract
Abstract Over 11% of Canadian students are currently enrolled in French immersion (FI) – a program where French is a subject of study and is the language of instruction in at least two content areas. Research shows that stakeholders in FI initial teacher education (ITE) programs identify French language proficiency development as an area of high priority; however, Canadian ITE programs do not typically provide linguistic support. This article reports on an adaptation and implementation of the Common European Framework of Reference (CEFR) (specifically, the European Language Portfolio [ELP]) as part of a remedial 24-week French writing course in an FSL ITE program focused on developing French proficiency. Student-teachers (n = 25) and the course instructor identified strengths and challenges associated with this initiative via surveys and interviews. Findings show participant convergence and divergence on the portfolio experience, raising implications for decision-making related to its use in ITE programs targeting FI teachers.
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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 | 0.034 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 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".