Adapting to the Ethics of Differentiated Learning Assessment: Analysis of Foreign-trained Teachers’ Experiences in Quebec
Bibliographic record
Abstract
In the last decade, due to the lack of teachers in Quebec, the province has welcomed a significant number of foreign-trained teachers (MEES, 2018). Research on their learning assessment skills shows that, for those teachers who get used to the standards and values of the culture of assessment for sanction in their native countries, taking into account the professionnal conventions in their host environment is a major issue to their socio-professional integration (Morrissette & Demazière, 2018a). Drawing on the theoretical approach of the social justice of Rawls (1971), we conducted a collaborative research with a group of six teachers trained in foreign countries from “meritocratic” backgrounds, to shed light on their adaptation to the ethics of differentiated assessment. The analyzes suggest a consentement that developped under the rhythm of negotiated identity conversion process through a socialization of resourcefulness in four phases: negation, discovery, learning, involvement.
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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 | 0.022 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.001 | 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".