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Record W2766830049

Early French immersion in British Columbia: A Consideration of the 'Struggling Learner'

2016· article· en· W2766830049 on OpenAlexaboutno aff
Chandra N. Hunt, Greg Ashman, Megan M. Short

Bibliographic record

VenueeCite Digital Repository (University of Tasmania) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsnot available
Fundersnot available
KeywordsFrench immersionMathematics educationPhenomenonPedagogyAP French LanguageContext (archaeology)PsychologyForeign languageHistory
DOInot available

Abstract

fetched live from OpenAlex

Early French Immersion (EFI) is a popular optional education program offered inmost of the 60 school districts in British Columbia (BC), Canada. Though districtshave varying policies, the model generally involves entry into the program inKindergarten-Grade 1 where French is the language of instruction for all subjects.There are no prerequisites to enrolment other than the students age, available space,and parental choice. In the first years of EFI, French is one hundred percent thelanguage of instruction.The problem being investigated and reported upon is a result of a recurring andperplexing personal observation of a small cohort of learners in the researchersGrade 2 classroom. These learners presented a disparate profile that is irrespective ofability, but that shares one thing: the learners repeatedly struggle to meet expectationsdespite the teachers best efforts.The investigation aimed to determine if this is a phenomenon experienced byother teachers, and if it is, to initially open the discussion about these students, beginto understand the reasons behind the struggling, and identify and initiate ways tobuild the learners success and well-being. Specifically, this chapter will consider thequestion: Within the BC classroom context, to what extent are teachers identifyingstudents who struggle in Early French Immersion?

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.200
Teacher spread0.190 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueeCite Digital Repository (University of Tasmania)Same topicWriting and Handwriting EducationFrench-language works237,207