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Record W3214536686 · doi:10.52358/mm.vi8.260

Les défis de la gestion de classe virtuelle synchrone

2021· article· fr· W3214536686 on OpenAlexaffvenueabout
Isabelle Carignan

Bibliographic record

VenueMédiations et médiatisations · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversité TÉLUQ
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

L’enseignement en ligne en mode synchrone a apporté son lot de défis pour les enseignants du primaire et du secondaire depuis le début de la pandémie de COVID-19 en mars 2020. Basé sur des observations réalisées auprès de 10 classes du primaire et du secondaire au Québec et en Ontario, ainsi que sur des discussions avec des enseignants, cet article de réflexion présente quelques constats sur la gestion de classe, qui semble beaucoup plus ardue à faire en ligne qu’en présence. Enseigner virtuellement demeure donc une solution d’urgence si la situation l’oblige. Autrement, l'enseignement en personne demeure ce que nous pouvons offrir de mieux aux élèves.

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)0.007
metaresearch head score (Gemma)0.021
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0090.005
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.003

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 head0.027
GPT teacher head0.338
Teacher spread0.311 · 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
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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Citations1
Published2021
Admission routes3
Has abstractyes

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