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Record W2046294919 · doi:10.1177/1367006910367848

First and second language knowledge in the language classroom

2010· article· en· W2046294919 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Bilingualism · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsConcordia University
Fundersnot available
KeywordsVariety (cybernetics)AP French LanguageCurriculumSecond-language acquisitionIsolation (microbiology)Class (philosophy)PsychologyFrenchComprehension approachLinguisticsLanguage assessmentSecond languageLanguage acquisitionLanguage educationPedagogyMathematics educationComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This feasibility study investigated how language instruction can be designed to help learners build on first language (L1) knowledge in acquiring a new language. It seems likely that learners will benefit from activities that draw their attention to features of their L1, but attempts to bridge the first and second language (L2) curricula often break down because the teachers typically work in isolation and are uncertain how to proceed. We attempted to address these problems by designing a series of cross-linguistic awareness (CLA) activities to be implemented on a trial basis with 48 young francophone learners of English (age 9—10 years) at a school in Montreal, Quebec. We observed language instruction in their French (L1) classes and identified features and themes that lent themselves to reinvestment in their English (L2) classes. Then 11 CLA teaching packages were developed and piloted with in an intensive year-long English as a second language (ESL) program. Classroom observations, interviews with both L1 and L2 teachers, and learner journal responses indicated that the activities were well received and that CLA instruction can usefully address a wide variety of linguistic features. Problems highlighted by the study are discussed; we also outline new research that will explore whether this promising experimental pedagogy leads to distinct language learning benefits.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.298
Teacher spread0.282 · 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