Teachers’ beliefs about students with learning disabilities in French Immersion : a phenomenological study
Bibliographic record
Abstract
French Immersion (FI) is a popular program designed for students to acquire proficiency in French. The FI model has been praised as a successful approach to additional language learning and criticized for perpetuating inequities. Evidence suggests that students with learning disabilities (LDs) can succeed in FI with proper support, yet they are often excluded from the program. To date, there is limited research on FI classroom teachers’ beliefs about the inclusion of students with LDs and the accessibility of FI programs for them. In this study, a hermeneutic phenomenological approach was implemented to explore teachers’ beliefs about the inclusion of students with LDs in FI. Six FI public elementary school teachers from a school district in British Columbia, Canada, were interviewed in a three-part series. During the interviews, the six teachers shared and reflected upon their beliefs, experiences, and perspectives about teaching students with LDs in FI. In analyzing the interviews, teachers identified barriers within FI that made the program inaccessible for students with LDs. Findings also surfaced specific personal factors (e.g., knowledge and teaching self-efficacy), student factors (e.g., motivation), and contextual factors (e.g., administration and district support) that impacted and influenced participants’ beliefs about the inclusion of students with LDs in FI. The teachers also offered suggestions and insights to make the program more inclusive. This study offers methodological implications for advancing future research in LDs in FI. It also suggests practical considerations for education stakeholders such as administrators, school boards, Ministries of Education, and teacher education programs to rethink the FI program through a more inclusive and accessible framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| 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".