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Record W2039515141 · doi:10.1558/wap.v1i1.37

Pedagogical Applications of a Second Language Writing Model at Elementary and Middle School Levels

2010· article· en· W2039515141 on OpenAlexaffabout
Paula Kristmanson, Joseph Dicks, Josée Le Bouthillier

Bibliographic record

VenueWriting & Pedagogy · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAction researchMathematics educationPedagogyPsychologyComputer scienceSociology

Abstract

fetched live from OpenAlex

This article describes an action research project conducted at two public schools in an urban center in the province of New Brunswick in eastern Canada. The project involved the development of and experimentation with a model for the instruction of writing (ÉCRI – écriture cohérente et raisonnée en immersion) at both the elementary and middle-school levels. Research questions focused on gaining insight into best practices for teaching writing through practitioner dialogue in professional learning communities (PLCs), classroom observation and videotaping, teacher reflections, and stimulated recall. The data gathered were analyzed to determine similarities and differences between the implementation of the model in elementary and middle school settings as well as second-language and first-language learning contexts. Results of the study demonstrate the applicability of this multi-phase model at both levels and in both learning environments and the adaptations necessary to meet the needs of learners in these contexts.

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)0.006
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 score0.008
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.089
GPT teacher head0.345
Teacher spread0.256 · 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

Citations13
Published2010
Admission routes2
Has abstractyes

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