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Record W2897866064 · doi:10.1522/rhe.v1i1.506

L’apprentissage de la programmation : Par quoi commencer et dans quel ordre?

2018· article· fr· W2897866064 on OpenAlexaffvenue
Patrick Giroux, M. Boivin, Vincent Porta Scarta

Bibliographic record

VenueRevue hybride de l éducation · 2018
Typearticle
Languagefr
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical scienceArt

Abstract

fetched live from OpenAlex

Les technologies occupent une part de plus en plus importante dans nos vies et la programmation est une compétence qui gagne en importance. De nombreux enseignants du préscolaire, du primaire et du secondaire intègrent des activités d’apprentissage de la programmation dans leurs activités en lien, notamment, avec les mathématiques. Ce texte a comme objectif d’aider les enseignants à planifier des activités de formation à la programmation en définissant les principaux concepts à maitriser pour apprendre à programmer, en suggérant un ordre fondé sur l’expérience et en donnant des exemples de stratégies ou d’activités pour initier les jeunes à la programmation.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.086
GPT teacher head0.458
Teacher spread0.372 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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