Effective practices for building an online French immersion program
Bibliographic record
Abstract
Bilingualism is part of Canada’s identity and its education system. Throughout the country, students have the option to learn in English or French. French Immersion is an option available for anglophones to learn the second Canadian official language. In the last fifteen years, this option for students has grown in popularity. The same can be said about online learning which provides educational opportunities to students beside attending a face-to-face classroom. However, the language used to deliver online course is primarily in English, except for virtual schools available only to “right holder” students. Currently in Canada, there are no online French Immersion program being offered to students. To correct this inequality, a website was created to introduce the benefits of online learning to school districts and to provide course design and teaching guidelines to French Immersion teachers as well as a sample of a Français Langue Seconde course. In order to build the website, it required bringing together my own professional experience and research on effective practices in teaching in French Immersion and teaching online. Although traditionally languages are taught in a face-to-face classroom, the website shows that with some thinking outside the box, it is possible for students to communicate in French, to improve their 21st-century skills, and to progress in their goal to become bilingual while studying online.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".