From Exclusion to Inclusion: Meeting the Needs of Struggling Learners in the Primary Level French Immersion Classroom
Bibliographic record
Abstract
The French Immersion program is popular in many school boards across Canada, but the attrition of learners experiencing difficulty has often been criticized. While the suitability of the program for all learners has been questioned, an emerging body of research suggests that this practice runs counter to a philosophy of inclusion and that students with diverse learning needs can be successful in immersion programs. This qualitative study explores the insights and perceptions of three practicing classroom teachers and one teacher educator who described their experiences working with struggling learners in the primary level French Immersion classroom. While some participants described having observed exclusionary practices, they all believed that everyone should be able to try French Immersion. Some nevertheless understood the program to be a better fit for some students than for others. Analysis of both the existing research and the data collected through this study suggest that the social and emotional well-being of a student plays a critical role in identifying and supporting struggling learners through differentiated instruction and in making decisions regarding their placement in the program.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".