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Record W4405430176 · doi:10.7202/1115072ar

Les stratégies de <i>coping</i> et le sentiment d’efficacité personnelle face aux évaluations sommatives

2024· article· fr· W4405430176 on OpenAlexvenueno aff
Alexandre Mabilon

Bibliographic record

VenueMesure et évaluation en éducation · 2024
Typearticle
Languagefr
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Cet article tente d’appréhender les stratégies de coping déployées par les adolescents dans le cadre des évaluations sommatives (Zimmer-Gembeck & Skinner, 2016) et d’approfondir la relation entre ces stratégies, le stress ressenti et le sentiment d’efficacité personnelle (Bandura et al., 2003) perçu par une population en pleine période de développement. Les données sont issues de mesures autorapportées auprès d’un échantillon de 660 élèves de l’enseignement secondaire. Les résultats montrent que l’investissement dans un style de coping (Connor-Smith & Flachsbart, 2007) axé sur la résolution du problème perçu et la recherche de soutien social favorise l’amoindrissement du stress ainsi que le développement du sentiment d’efficacité personnelle. La recherche permet de mettre en évidence les défis liés au stress et à sa gestion face aux activités stressantes que représentent les évaluations sommatives. Elle offre également l’occasion de souligner le rôle de l’environnement d’apprentissage dans l’utilisation des évaluations sommatives afin de limiter les conséquences négatives pour l’apprentissage des adolescents.

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)0.002
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.111
GPT teacher head0.482
Teacher spread0.371 · 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
Published2024
Admission routes1
Has abstractyes

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