ANTICIPATING FUTURE NEEDS IN FRENCH IMMERSION PROGRAMS WHERE NO TEXTBOOKS ARE USED
Bibliographic record
Abstract
Problem:The Ministry of Education of Ontario usually lists authorized textbooks for use in schools in a document called The Trillium List (2019). There is however, a lack of titles for French immersion. This creates a number of issues. It is hard to have consistency within and across programs when teachers do not know what learners covered during the previous year. What is agreed upon, in Ontario second language education, is the adoption of the action-oriented communicative approach as delineated in Council of Europe documents (CEFR).The research:Objectives were1. To identify in the teacher preparation program, preparedness in terms of language proficiency and capability to adapt to future learners’ language use level. In light of such issues, the course outline is based on forecasting needs. Not only is the instructor required to get a good grasp of the student’s capabilities in the course, mostly as regards ability to use the French language, but also figure out at what level future learners will be able to use the language.2. To establish competencies to enact the communicative-action-oriented perspective as mandated by the Ministry (2014).The future teachers were required to establish their own language passports, which were analyzed first. Then, based upon the levels of ability, action-oriented tasks were designed in groups. These came under scrutiny to assess both pedagogical thinking and future possibilities of expansion and adaptation for in-class use during the future school placements.Method:The method used is qualitative as it best allows to scrutinize for individual details and follow-through with observational data collection over time. The researcher was the course instructor and notes were taken in a journal during and after each class meeting. Assignments were also examined and notes taken on them as relevant to the objectives of this research.To establish language ability, the future teachers established their own language passports, which were analyzed first. In addition observational notes were taken during class on language use and as well while the future teachers were preparing language activities for learners at different levels. Then, based upon the levels of ability, and an examination of Ministry Curriculum guidelines (2013, 2014) action-oriented tasks were designed in groups. These came under scrutiny to assess both pedagogical thinking and future possibilities of expansion and adaptation for in-class use during the future teachers’ practicum placements.An analysis of final assignments around the creation of a teaching unit was carried out and these findings will also be reported.Results:Various participants experienced some difficulties with unit development. If fluidity in language use was a limitation, it appears that participant initiative and commitment to work and the seriousness of effort, were more important factors in measuring success. Indeed those who consulted more with the instructor, explored various avenues and one future teacher who even restarted on a new path from the beginning, were more successful.We will present a detailed successful unit of analysis showing positive aspects as well as concerns around decision making and action-orientation in the pedagogical unit developed. References will be made about similar units and those that greatly differ in quality will be expanded upon with suggested pathways for improvement and explanations for the causes of deviations.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".