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Record W6931598936 · doi:10.5281/zenodo.5752156

Regard de futurs enseignants sur l'importance des compétences TIC (Internet) pour les jeunes et la responsabilité de divers intervenants à cet égard = Perceptions of teachers-in-training on the importance of ICT (Internet) skills for youth and the responsibilities of education stakeholders for ensuring them

2014· article· fr· W6931598936 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2014
Typearticle
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsnot available
Fundersnot available
KeywordsInformation and Communications TechnologyLikert scalePosition (finance)PerceptionScale (ratio)

Abstract

fetched live from OpenAlex

Résumé Au 21e siècle, les compétences « TIC » sont importantes pour l’intégration des individus à la société et la compétitivité des nations. Plusieurs nations ont d’ailleurs ajusté leurs curriculums, attribuant cette responsabilité à l’école. Mais qu’en pensent les futurs enseignants? Considèrent-ils qu’il revient à l’école de prendre en charge le développement de ces compétences? À cet égard, nous avons demandé à 328 futurs enseignants suisses, français et québécois de se positionner, à l’aide d’une échelle de Likert, quant à l’importance de 21 compétences/connaissances TIC et de nous préciser qui devrait, selon eux, être responsable de l’encadrement du développement de chacune. Summary In the 21st century, « ICT » skills are important for the integration of individuals into society and the competitiveness of nations. Several nations have adjusted their curricula, assigning this responsibility to the school. But what do pre-service teachers think? Do they believe it is for the school to support the development of these skills? In this regard, we asked 328 student teachers from Switzerland, France and Quebec to position themself about the importance of 21 ICT skills/knowledge using a Likert scale and tell us who should, according to themselves, be responsible for supervising the development of each.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.070
GPT teacher head0.275
Teacher spread0.205 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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