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Record W4396234611 · doi:10.18162/fp.2023.847

Le mentorat des primants à l’ULiège : freins et leviers à la participation étudiante

2023· article· fr· W4396234611 on OpenAlexvenueno aff
Johanne Huart, Dominique Verpoorten, Pascal Detroz, Geneviève Philippe, Benoît Donnet, Guénaël Devillet, Sabine Geerts, Laurent Leduc

Bibliographic record

VenueFormation et profession · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

En dépit des efforts déployés par les universités pour accompagner les étudiants de première année, il arrive que ceux-ci sous-exploitent les dispositifs pédagogiques conçus à leur intention. Confrontée à ce phénomène, l’Université de Liège s’est penchée sur les freins et les leviers à la participation des primants à un dispositif de mentorat par les enseignants, en recourant à la théorie du comportement planifié. Les résultats montrent l’importance de la représentation qu’ont a priori les étudiants de l’expérience du mentorat et de leur sentiment d’être capable d’y participer, et pointent des croyances relatives à l’attachement, aux mentorés, aux mentors et à l’organisation du dispositif.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.003
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 head0.304
GPT teacher head0.522
Teacher spread0.217 · 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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

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