The First Ten Days of Literacy Instruction in the Junior French Immersion Classroom: A Lesson Plan and Guide to Achievement
Bibliographic record
Abstract
French Immersion enrolment is becoming increasingly popular for families interested in immersing their children in a second language (Canadian Parents for French, 2023). At the same time, a public inquiry on literacy achievement, the Right to Read Report, has highlighted the need for effective literacy instruction among regressing reading achievement in the province of Ontario (OHRC, 2019). This report has pushed the Ministry of Education to restructure its literacy programs to reflect appropriate teaching practices (Ontario Ministry of Education, 2024). Despite these findings, there is a lack of appropriate resources for literacy instruction in French Immersion classrooms, particularly in the junior grades (Grades 4-6). The purpose of this project is to address this gap by creating a 10-day lesson plan that is meant to set up a successful literacy program in the junior classroom. By using the Scarborough Reading Rope (2001) as an instructional framework, the lesson plan addresses the integral components of literacy achievement: phonemic awareness and phonics, reading fluency, oral language, listening and reading comprehension, vocabulary and morphology. This project also considers the nuances of teaching in a French Immersion setting and offers guidelines on improving literacy instruction in a language learning context. Ultimately, this project aims to support French Immersion educators in their literacy instruction journey by providing a practical resource to set the school year up for achievement.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".