Supporting the development of senior secondary French Immersion students’ French as a second language and learner autonomy through self-directed form-focused metacognitive listening activities
Bibliographic record
Abstract
This study examines the effect of teaching strategies in self-directed form-focused metacognitive listening exercises to Grade 11 French Immersion (FI) students. The objective is to prepare students to autonomously maintain their French as a second language (FSL) skills after leaving classroom instruction at graduation, thus preventing potential attrition of their FSL. A mixed-methods approach is used to examine development in FSL competency and learner autonomy. Principal theoretical frameworks are: L2 Input Processing Theory; Metacognitive Awareness; Sociocultural Theory; Complex Dynamic Systems Theory; and Self-directed Learning Theory. Study findings show senior FI students are interested in maintaining their FSL skills autonomously. Speaking French is an important part of their identity. Participants responded positively to the study intervention. Data analysis indicates that self-directed form-focused metacognitive listening exercises produced statistically significant increases in listening and reading, and statistically insignificant increases in writing and speaking. Participants noted significant development in their autonomy. Participants intend to continue to use the intervention strategies from this study into their future. Discussion links the findings to the literature review and offers suggestions for further research. It addresses considerations for the secondary FSL/FI classroom; Ontario FSL curriculum review; and additional FSL/FI stakeholders. Principal conclusions are that senior FI learners need and appreciate FSL form-focused instruction. They respond positively to instruction in metacognition and metacognitive listening and can combine their learning to successfully engage in self-directed form-focused metacognitive listening activities. Such activities support development of learner FSL and autonomy. This approach is appropriate as a potential remedy to the eventual attrition of FI graduates’ FSL skills. Overall, this study affirms the capacity of the late adolescent / senior FI learner to engage effectively in FSL self-directed learning and recognizes the unique character and variability of L2 learners in their experience of L2 acquisition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".