Playing with Possibilities: Drama and Core French in the Montessori Elementary Classroom in British Columbia, Canada
Bibliographic record
Abstract
French as a Second Language (FSL) is not often a popular subject among Canadian elementary and high school students. Negative attitudes and low motivation for learning French contribute to attrition at the high school level. In this article, an alternative teaching approach is applied to the Canadian FSL context at the elementary school level in the province of British Columbia. This action research study conducted in 2010 investigated the outcomes of using a drama-based approach to instruct Core French to 12 year-old students at a Montessori elementary (public) school in British Columbia, Canada. Ten students worked with a teacher/researcher twice a week over a six-week period, using drama strategies and improvisational activities to practice and improve their French language and literacy skills. The use of drama strategies proved motivational for the students who participated with enthusiasm and expressed a desire to continue learning French through drama. The action research approach allowed the students a greater degree of autonomy as their feedback was used to develop lesson content. Engagement in their own learning contributed to improved student attitudes towards attending French class. Ways of further implementing this teaching approach in elementary classrooms needs to be the subject of future research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".