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Record W2123370815 · doi:10.7202/039177ar

Persister dans la publication de son e-portfolio?

2009· article· fr· W2123370815 on OpenAlexaffvenue
Philippe Didier Gauthier, Annie Jézégou

Bibliographic record

VenueRevue internationale des technologies en pédagogie universitaire · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophyPortfolioEconomics

Abstract

fetched live from OpenAlex

L’étude à l’origine de cet article s’intéresse à une question encore peu abordée dans les travaux de recherche sur le e-portfolio : la persistance ou la non-persistance dans la publication de son portfolio sur Internet. Elle traite cette question en vérifiant le rôle joué ici par la perception d’efficacité personnelle d’étudiants de l’enseignement supérieur pour mener à bien leur projet professionnel et pour développer techniquement leur e-portfolio. Elle aborde également cette question en dévoilant le rôle joué par leur perception de l’utilité de persister dans la publication de ce e-portfolio.

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)0.026
metaresearch head score (Gemma)0.139
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.139
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0140.012
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.004

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 head0.033
GPT teacher head0.338
Teacher spread0.305 · 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.

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

Citations5
Published2009
Admission routes2
Has abstractyes

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