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Record W6894072011 · doi:10.5281/zenodo.5604572

Comparaison de la perception des exigences professionnelles par les futurs enseignants du primaire à la fin des première, deuxième et troisième années de formation à l'enseignement à Zurich (Suisse)

2021· article· fr· W6894072011 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)PerceptionOccupational trainingCohortLongitudinal study

Abstract

fetched live from OpenAlex

Nous présentons les résultats d’une recherche réalisée auprès de futurs enseignants de Zurich (Suisse) et basée sur une approche longitudinale comptant trois sessions de collecte de données. Pour ce faire, 153 étudiants d’une seule cohorte ont répondu à un questionnaire à trois moments de leur formation: en première, deuxième et troisième année. L’outil EABest-K (Keller- Schneider, 2014) comporte 29 questions couvrant sept domaines d’exigences professionnelles évaluées chacune sous trois angles par les étudiants: le degré de sollicitation d’une exigence, le sentiment de compétence vis-à-vis de cette exigence et la perception de sa pertinence. Nous concluons avec des pistes pour une recherche consécutive canado-suisse. <em>(English version)</em> <strong>Comparison of Future Teachers’ Perception of Professional Requirements at the End of Year One, Two and Three of Their Primary Teacher Education Program in Zurich (Switzerland)</strong> We present the results of a research conducted among future Swiss teachers from Zurich (Switzerland). Based on a longitudinal approach involving three sessions of data collection, 153 students from a single cohort completed a questionnaire at three points during their teacher training: in the first, second and third year. The EABest-K tool (Keller-Schneider, 2014) consists of 29 questions covering seven areas of professional requirements, each evaluated from three angles by the students: the degree to which a requirement is considered as a challenge, the experience of competence with regard to this requirement and the perception of its relevance. We conclude with avenues for a consecutive Canadian-Swiss research project.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.087
GPT teacher head0.314
Teacher spread0.227 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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