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Record W6892592498 · doi:10.5281/zenodo.10456714

Examen de las opiniones de futuros profesores de francés sobre su participación en un proyecto telecolaborativo internacional de escritura de relatos multilingües digitales

2023· peer-review· fr· W6892592498 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typepeer-review
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEthnic discriminationOccupational trainingSocial impactContext (archaeology)

Abstract

fetched live from OpenAlex

L’objectif de cette étude était d’examiner les opinions de futurs enseignants de français langue seconde (FLS) ou langue étrangère (FLE) concernant leur participation à un projet international (Québec-Espagne) de télécollaboration pour la création d’histoires multilingues numériques. En équipes, les futurs enseignantsdes deux classes internationales ont écrit ensemble des histoires en français qui ont ensuite été traduites dans d’autres langues parlées par les participants et publiées sur la plateforme Wix. Grâce à un questionnaire administré à la fin du projet, le processus d’écriture des histoires, le travail d’équipe et l’opinion générale du projet ont été analysés. Les résultats ont montré que la production d’histoires multilingues numériques a permis aux participants de développer différentes compétences didactiques. Afin de mieux comprendre les tensions apparues au cours du projet, les résultats sont discutés sous l’angle de la théorie de l’activité (Engestöm, 2001).

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)0.008
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.003

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 head0.064
GPT teacher head0.356
Teacher spread0.293 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicFrench Language Learning MethodsFrench-language works237,207