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Record W4404645658 · doi:10.5206/eei.v34i2.17262

Teacher Confidence in Meeting Students’ Needs in French as a Second Language Classes

2024· article· en· W4404645658 on OpenAlexaffvenueabout
Robert T. Grant, Callie Mady

Bibliographic record

VenueExceptionality Education International · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMathematics educationPsychologyPedagogy

Abstract

fetched live from OpenAlex

In past practice in Ontario, Canada, students with learning difficulties have been afforded sporadic access to French as a second language (FSL) learning opportunities, contributing to limited exposure and preparation of teachers to meet the needs of these students. A change in policies now requires the inclusion of all students. In order to support students with learning difficulties in meeting with success, FSL teachers have repeatedly made it clear that they would appreciate professional development opportunities. This study used a collaborative-inquiry process to offer FSL teachers four professional development sessions on the topic of meeting the varied needs of students. Pre and post questionnaires and post interviews showed that the teachers gained confidence in their use of strategies to support students’ French comprehension and production. Participating FSL teachers highlighted the importance of not only the knowledge gained but also the opportunity for collaboration. In addition to gaining knowledge of and confidence in meeting the needs of students with learning difficulties, the FSL teachers were assured enough to question decisions on excluding such learners from second-language learning opportunities.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0340.001

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 head0.024
GPT teacher head0.351
Teacher spread0.327 · 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 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
Published2024
Admission routes3
Has abstractyes

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