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Record W1902851849

Intégrer l’éducation technologique à l’éducation scientifique : pertinence pour les élèves et impacts sur les pratiques d’enseignants

2012· article· fr· W1902851849 on OpenAlexaffvenueabout
Mathieu Lacasse, Sylvie Barma

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2012
Typearticle
Languagefr
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt
DOInot available

Abstract

fetched live from OpenAlex

Cette recherche collaborative, qui s’est deroulee pendant plus de quinze mois, s’interesse aux defis que presente, pour les enseignants, l’integration du travail en classe-atelier a l’enseignement des sciences dans un contexte de reforme de programme d’etudes au 2e cycle du secondaire au Quebec. Cet etat des faits a justifie la mise en place d’un travail de collaboration entre plusieurs intervenants du milieu scolaire, et plus particulierement avec deux praticiens reflexifs qui ont modelise, avec l’equipe de recherche, deux situations d’apprentissage et d’evaluation (SAE) integrant le travail en classe-atelier a l’enseignement des sciences : ceci dans le but de former leurs pairs a l’approche d’enseignement qu’ils proposaient en coherence avec les prescriptions du programme scolaire quebecois. A la suite de deux sessions de formation, des enseignants ayant accepte de mettre en oeuvre ces SAE nous ont fait part des conditions favorables et des contraintes liees a leur mise en place. Cette recherche documente egalement les motivations des enseignants a integrer la technologie alors qu’ils abordent le theme des eoliennes et de l’electronique avec les eleves dans l’intention de contextualiser l’enseignement et d’augmenter l’interet de ces derniers. Mots cles : Classe-atelier, enseignement au secondaire, pratiques didactiques, sciences, technologie.

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)0.017
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.134
GPT teacher head0.382
Teacher spread0.248 · 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.

Study designQualitative
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

Citations2
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Education / Revue canadienne de l éducationSame topicInnovative Teaching and Learning MethodsFrench-language works237,207