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Record W2121170563 · doi:10.1177/1362168807086286

Looking beyond teachers' classroom behaviour: Novice and experienced ESL teachers' pedagogical knowledge

2008· article· en· W2121170563 on OpenAlexaff
Elizabeth Gatbonton

Bibliographic record

VenueLanguage Teaching Research · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsConcordia University
Fundersnot available
KeywordsPsychologyMathematics educationKnowledge levelPedagogyTeacher educationProcedural knowledgeTeaching methodBody of knowledge

Abstract

fetched live from OpenAlex

This paper reports a study that examined the categories of pedagogical knowledge (knowledge related to the act of teaching) of novice ESL teachers as gleaned from their verbal reports of what they were thinking about while teaching and compared these categories to those found for experienced teachers in an earlier study (Gatbonton, 1999). The goal was to discover what pedagogical knowledge these learners have internalized after having completed a teacher-training program and how this knowledge compares to that of teachers who have had more experience than they have had. The novice and experienced teachers' pedagogical knowledge were examined specifically in relation to language management (how to handle language input and student output), procedural issues, and handling student reactions and attitudes. The results of the study show that the pedagogical knowledge of novice teachers is comparable to that of experienced teachers in terms of major categories but not in terms of details within these categories. Implications for teacher training 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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.136
GPT teacher head0.414
Teacher spread0.278 · 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 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

Citations232
Published2008
Admission routes1
Has abstractyes

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