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Record W2617199915

Learning to Teach in an Intensive Introductory TESL Training Course: A Case Study of English Teacher Learning

2013· dissertation· en· W2617199915 on OpenAlexaboutno aff
Danielle Freitas

Bibliographic record

VenueTSpace · 2013
Typedissertation
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumPerspective (graphical)Transformative learningMathematics educationSociocultural perspectivePsychologyPedagogyTeacher educationQualitative researchSociocultural evolutionComputer scienceSociology
DOInot available

Abstract

fetched live from OpenAlex

Despite a growing body of research on trainee teachers’ learning during pre-service programs, intensive introductory TESL training courses are still designed to instruct a “standard” type of trainee teacher. This research study investigates the factors that mediate trainee teachers’ learning process as well as the interaction between these factors, which either facilitate and/or hinder trainee teachers’ success during an intensive introductory TESL training course. Using a qualitative holistic single-case study, informed by an interpretivist perspective, this study explores how three trainee teachers learned how to teach during a course in Southern Ontario, Canada. An integrated conceptual framework, formed by a sociocultural perspective of teacher learning, a holistic view of curriculum, and transformative pedagogy was employed and the findings include four major factors that mediated trainee teachers’ teacher learning process and three types of interaction that facilitated and/or hindered their success during the program.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.035
GPT teacher head0.325
Teacher spread0.290 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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