Assessment dynamics at play in a collaborative research project with middle-school teachers in France
Bibliographic record
Abstract
This study deals with the dynamics of assessment at play in collaborative research carried out with two multidisciplinary teams of French middle-school teachers. It shows how connecting the teachers’ experience with the outside frame of reference, through a reflexive, critical, but also prospective approach of assessment for learning (AfL) methodology, produces both referentialization and subjectification/intersubjectification, enabling individual and collective professional development. Collective creation of a common frame of reference through students’ development and usage of criteria assessment grids brings about varied implementations and understandings among teachers when the assessment is actually conducted. Experimenting with this hybrid construct in the classroom and discussing it by confronting the activity’s actual outcome with its projected result open new insights and perspectives that lead to a broader referentialization of AfL and renewed professional identity.
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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 | 0.030 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".