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Record W7160337353 · doi:10.7202/1124956ar

Croiser les regards sur les pratiques enseignantes en cours magistral : analyse, validation et comparaison de trois instruments de mesure

2025· article· fr· W7160337353 on OpenAlexvenueno aff
Amélie Duguet, Mikaël De Clercq

Bibliographic record

VenueMesure et évaluation en éducation · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsIndependence (probability theory)Identity (music)Measure (data warehouse)ESPACE

Abstract

fetched live from OpenAlex

Cet article propose d’apporter un éclairage nouveau sur les pratiques pédagogiques des enseignants universitaires en cours magistral. Il s’agit, à partir de données collectées au sein d’une université française auprès d’un échantillon de 1 250 étudiants et de 39 enseignants, d’éprouver, d’une part, la validité et la fidélité de trois instruments de mesure des pratiques (observées, autorapportées et perçues) et, d’autre part, d’étudier les différences de perception de ces pratiques en fonction de la mesure employée. Les résultats nous amènent à conclure à une bonne fiabilité des instruments, en distinguant trois dimensions des pratiques. De même, des analyses intrasujets et multiniveaux permettent de relever des différences significatives de description des pratiques en fonction de l’instrument utilisé. L’ensemble des résultats est discuté pour montrer la complémentarité potentielle d’un regard croisé sur les pratiques enseignantes et les limites respectives des instruments isolés.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.040
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.087
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.142
GPT teacher head0.476
Teacher spread0.333 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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