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Record W2472211083

From Teacher Candidates to ESL Ambassadors in Teacher Education.

2005· article· en· W2472211083 on OpenAlexaboutno aff
Clea Schmidt

Bibliographic record

VenueTeaching English as a Second or Foreign Language--TESL-EJ · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsProfessional developmentTeacher educationPedagogyCurriculumSession (web analytics)Context (archaeology)Faculty developmentMathematics educationPsychologySociologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

This paper analyzes the process and impact of a pre-service teacher education course assignment that engaged teacher candidates in developing and delivering an ESL professional development night for faculty colleagues and teachers from the field. The night involved a reader's theatre performance and follow-up discussion of Tara Goldstein's (2003) play Hong Kong, Canada, exploring issues facing students and teachers in a multilingual high school, as well as a resource display containing contentbased ESL lessons and resources developed by the candidates. Feedback received from teacher candidates who organized and led the session suggests that the evening was successful in enhancing candidates' ESL-related and professional confidence, and helping them apply learning from the course in practical and meaningful ways. Situating findings within the context of ESL teacher education in Manitoba, implications for collaborative curriculum development and bridging the theory/practice divide are discussed.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.002
Scholarly communication0.0060.002
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0280.006

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 head0.011
GPT teacher head0.266
Teacher spread0.255 · 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 designNot applicable
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

Citations1
Published2005
Admission routes1
Has abstractyes

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