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Record W4285579781 · doi:10.4000/adsc.566

Savoirs véhiculés par les manuels scolaires français et québécois à propos de l’aire. Une étude comparative

2020· article· en· W4285579781 on OpenAlexaboutno aff
Nathalie Silvia Anwandter Cuellar, Steve Tremblay

Bibliographic record

VenueAnnales de didactique et de sciences cognitives · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationPraxeologySociologyPedagogyHumanitiesEpistemologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This article presents a comparative study of French and Quebec textbooks on the notion of area. Several research studies have raised students’ difficulties in understanding the concept of area, and recent work suggests studying these difficulties in connection with the learning opportunities offered by textbooks, which are a tool widely used by teachers. In order to highlight the similarities and differences in the knowledge set out in the textbooks of two territories and to interpret them according to the learning of the pupils, we have built a praxeological reference model using the Anthropological Theory of Didactics (TAD). Our results show similar limitations in French and Quebec textbooks, in particular the strong focus on the numerical dimension of the area to the detriment of the elements contributing to a conceptualization of this notion.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.104
GPT teacher head0.410
Teacher spread0.306 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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