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Record W3200601406 · doi:10.21432/cjlt28098

Enseignement et évaluation des mathématiques à distance durant la Covid-19

2021· article· fr· W3200601406 on OpenAlexaffvenue
M. Tremblay, Anne-Michèle Delobbe

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Humanities2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Valuation (finance)ArtMedicineVirology

Abstract

fetched live from OpenAlex

La pandémie liée au coronavirus SARS-CoV-2 a entraîné une multitude de mesures visant à contrer sa propagation. Parmi elles, la fermeture des établissements scolaires et le passage non-planifié à l’enseignement à distance. Le présent texte porte son attention sur l’expression de la dynamique d’enseignement-apprentissage-évaluation (mai-juin 2020) en mathématique auprès de 311 enseignants primaire et secondaire. Les résultats dégagent cinq principaux enjeux identifiés par les répondants. L’activité mathématique menée sous la modalité synchrone est davantage discuté et on y constate la place importante prise par l’exposé magistral et la résolution de problèmes issus de manuels. Les objets retenus par les enseignants dans l’exercice du jugement en évaluation surprennent et semblent teintés par différentes décisions ministérielles.

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 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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.351
Teacher spread0.314 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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".

Quick stats

Citations4
Published2021
Admission routes2
Has abstractyes

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