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Record W2132219273 · doi:10.7202/1015065ar

Usages des technologies en éducation : analyse des enjeux socioculturels

2013· article· fr· W2132219273 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueÉducation et francophonie · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article propose une analyse des enjeux socioculturels qui accompagnent les usages des technologies en éducation. Nous commençons par relever que, malgré leur pertinence éducative et socioprofessionnelle, les technologies en éducation doivent faire face à plusieurs défis, notamment parce qu’elles ne tiennent pas compte des usages technologiques des apprenants en dehors des institutions éducatives. Sur la base de ce constat, deux objectifs sont poursuivis : le premier consiste à dresser un portrait des usages technologiques des apprenants en dehors des institutions éducatives. Le second se propose d’en déduire des implications pour orienter les usages des technologies en contexte éducatif. Pour ce faire, nous procèderons dans un premier temps à une analyse des usages technologiques des jeunes. Nous en déduirons ensuite des implications pour orienter les usages des technologies en éducation, notamment en proposant un modèle « élargi » des technologies en éducation.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.005

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 head0.047
GPT teacher head0.356
Teacher spread0.309 · 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