Faute de mieux: An exploration of Core French curriculum, teaching methods, and learner motivational factors in British Columbia
Bibliographic record
Abstract
As French education rises in popularity across Canada, there is an increasing need to assess the impact of French curriculum and teaching methods on students. In 2023, the Canadian federal government updated the Action Plan for Official Languages, with up to $242.8 million funding an increase in the national English-French bilingualism rate by 2036. Across Canada, efforts are being made to accomplish Action Plan goals, including the British Columbian mandate that requires students to take a second language course from Grades 5 through 8. Despite this, very few studies have focused on the motivational factors that affect Core French students’ willingness to persevere in their French studies (Arnott, 2019; Carr, 2007; Trerice, 2015). Through both qualitative and quantitative methods including participant surveys, Likert scale rankings, and an interview, this study addresses this gap in the literature by investigating the factors that demotivate B.C. students from enrolling in Core French beyond Grade 8, and considers what can be done to mitigate these factors. This research focused on a group of Grade 8 students on Vancouver Island during their final mandatory Core French course, as well as two Core French instructors. Key findings of this study are that students are demotivated to continue studying French when they dislike the pedagogical materials used in class, experience feelings of anxiety or embarrassment during class time, and perceive their teachers’ French knowledge or skills to be inadequate. Additionally, teacher challenges include a lack of perceived standardized learning outcomes, a lack of available Core French resources, and insufficient pre-service teacher training. Results of this study have generated actionable recommendations to improve Core French pedagogy based on student and teacher perspectives, with the goal of fostering classroom environments in which students feel supported and motivated to continue learning French.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".