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Record W4214515128 · doi:10.52358/mm.vi9.243

Pratiques d’évaluation numérique chez le personnel enseignant : Vers le développement d’un instrument de mesure

2022· article· fr· W4214515128 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMédiations et médiatisations · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicEducational Tools and Methods
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceValuation (finance)SociologyPhilosophyBusiness

Abstract

fetched live from OpenAlex

L’article présente une synthèse de travaux effectués dans le cadre d’un stage doctoral à l’Observatoire des pratiques innovantes d’évaluation des apprentissages (OPIEVA) de l’Université du Québec à Montréal (UQAM). Le stage portait sur le développement d’un outil de mesure des pratiques d’évaluation numérique du personnel enseignant à tous les ordres d’enseignement. À partir d’une recension des écrits, 11 moyens de soutenir l’évaluation à l’aide du numérique ont été identifiés. Ces caractéristiques de l’évaluation numérique ont permis de créer, de concert avec l’équipe de l’OPIEVA, une première version d’un questionnaire. En plus de définir les caractéristiques de l’évaluation numérique et de présenter des items du questionnaire, cet article discute de la portée des travaux effectués pour la description des pratiques enseignantes avec le numérique.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.080
GPT teacher head0.356
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it