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Record W4391856378 · doi:10.4000/alsic.6774

Approches critiques des technologies en éducation et implications didactiques

2023· article· fr· W4391856378 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAlsic · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsUniversité du Québec à MontréalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsPsychologySociology

Abstract

fetched live from OpenAlex

Située à la croisée des approches critiques en didactique des langues et de celles des technologies en éducation, l’étude des technologies en didactique des langues (voir, par exemple, Warschauer, 1998 ; Ollivier, 2019) dispose d’assises critiques complémentaires pour assurer son développement, si tant est qu’une masse suffisante de chercheur.ses travaillent à les structurer davantage. Dans le cadre de ce texte, nous proposons de nous focaliser sur les approches critiques des technologies en éducation, en tant qu’approches contributives de l’étude critique des technologies en didactique des langues. Pour ce faire, nous commençons par poser quelques balises des approches critiques en général. Nous les mobilisons ensuite pour le cas des technologies en éducation, en les posant comme des voies de dépassement de deux conceptions courantes de la relation "technologies – éducation" : les conceptions instrumentalistes et technodéterministes. Pour en donner une vue plus tangible, nous présentons finalement un appareillage théorique parmi d’autres (voir Collin, 2022), qui appréhende l’innovation technopédagogique au croisement des approches critiques de la technique et des études du Social Shaping of Technology (SST).

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.080
GPT teacher head0.428
Teacher spread0.349 · 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