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Record W3130905655 · doi:10.18162/ritpu-2016-v13n23-12

Bilan de l’émergence des MOOC dans deux universités francophones

2016· article· fr· W3130905655 on OpenAlexaffvenueabout
Philippe Emplit, J. M. Blondin, Nicolas Roland, Bruno Poëllhuber

Bibliographic record

VenueRevue internationale des technologies en pédagogie universitaire · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Dans le contexte où les universités sont appelées à se positionner sur la question des MOOC, ce texte présente le contexte institutionnel de l’intégration de cours en ligne massivement ouverts au sein de deux établissements universitaires : l’Université de Montréal et l’Université libre de Bruxelles. Cette étude de cas de pratiques de gestion, réalisée à partir du point de vue des acteurs principaux, fait état du contexte, du processus ayant mené aux objectifs stratégiques et du positionnement de chacun des établissements, et rend compte de la mise en oeuvre de la stratégie retenue. Dans les deux cas, une approche gradualiste de l’innovation a été adoptée en faisant appel aux acteurs terrain et en arrimant une opération de recherche au développement des MOOC. La question de la qualité, les liens à établir avec les enseignements traditionnels et la reconnaissance des apprentissages réalisés constituent également des éléments centraux des préoccupations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.124
GPT teacher head0.372
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2016
Admission routes3
Has abstractyes

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Same venueRevue internationale des technologies en pédagogie universitaireSame topicEducation, sociology, and vocational trainingFrench-language works237,207