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Record W4391428271 · doi:10.52358/mm.vi19.397

Le syllabus de cours, un instrument au service de l’apprentissage et de l’enseignement

2024· article· fr· W4391428271 on OpenAlexaffvenue
Claire Peltier, Hugo Crovello, Isabelle Mirbel

Bibliographic record

VenueMédiations et médiatisations · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesSyllabusSociologyPsychologyArtPedagogy

Abstract

fetched live from OpenAlex

Cet article présente les résultats d’une recherche mixte menée à l’Université Côte d’Azur (France) autour de la mise en place des syllabus numériques. En tant qu’instruments au service de l’apprentissage des étudiants, les syllabus (ou plans de cours) sont susceptibles de favoriser une représentation convergente des intentions pédagogiques des enseignants et de la perception de celles-ci par les étudiants. Cette recherche rend compte des représentations que se font des syllabus les étudiants et les enseignants interrogés (par questionnaires et entretiens semi-directifs) et de leur perception du dispositif mis en place dans leur université. Les résultats mettent en lumière une divergence de point de vue entre les projections des enseignants et les attentes des étudiants. Ils soulignent la nécessité d’une meilleure compréhension des besoins des étudiants et de l’élaboration d’une représentation partagée de l’environnement d’apprentissage pour favoriser une expérience d’apprentissage réussie.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.035
GPT teacher head0.329
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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