Towards the adoption of a balanced approach to literacy instruction in LESLLA classrooms in Québec, Canada
Bibliographic record
Abstract
The current study reports on an action research project taking place in two Quebec adult education centres and aiming to create learning opportunities for LESLLA learners of French to pursue their literacy development journey beyond the advancement of their technical skills. More specifically, our research objective was to highlight the challenges and affordances faced by the participating teachers during the study in order to show how instructional change in favour of a more balanced approach to literacy instruction can occur during an action research project involving close mentoring for teachers. To do so, we first described the participating teachers’ meaning-focused literacy teaching practices during non-participant observation sessions in four teachers’ classrooms over the course of 6 weeks, totalizing 25 hours of observed teaching practices. Although the vast majority of all practices observed were code-focused, some instances of meaning-focused teaching practices were identified. During two training sessions, these practices acted as a starting point for exploring new meaning-focused practices that were then piloted with their students. We observed that, in the course of an action research project consisting of iterative cycles of reflection, action, and evaluation, implementing activities aligned with a more balanced approach to literacy instruction seems possible among teachers who typically rely on code-focused activities.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".