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Record W2030428498 · doi:10.3138/cmlr.56.4.585

Investigating Experienced ESL Teachers' Pedagogical Knowledge

2000· article· en· W2030428498 on OpenAlexvenueno aff
Elizabeth Gatbonton

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationQualitative researchQualitative analysisTransition (genetics)PedagogySociology

Abstract

fetched live from OpenAlex

This study investigated the hypothesis that it is possible to access the pattern of knowledge about teaching and learning (pedagogical knowledge) that experienced teachers utilize while they teach. This hypothesis was investigated through qualitative and quantitative analyses of verbal protocols obtained from teachers who simultaneously watched videotaped segments of themselves teaching and reported on thoughts they had as they taught these segments. Two sets of experienced teachers (N=7) uniformly reported 20 to 21 categories of pedagogical thoughts that they claimed were in their minds while teaching. Of these, seven to eight were reported more frequently than others. The lists of predominant categories for both sets are headed by thoughts concerned with managing both the language the students hear and the language they produce (Language Management). Thoughts about students (Knowledge of Students), thoughts about ensuring the smooth transition of activities in the classroom (Procedure Check), and assessing student participation in and progress with the classroom tasks (Progress Review) were also among those that featured highly on both sets of teachers' predominance lists. In terms of an approach in analyzing the thought processes of ESL teachers, the study suggests that a combination of qualitative and quantitative methods may be profitable.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.057
GPT teacher head0.288
Teacher spread0.231 · 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 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

Citations58
Published2000
Admission routes1
Has abstractyes

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Same venueCanadian Modern Language Review/ La Revue canadienne des langues vivantesSame topicEFL/ESL Teaching and LearningFrench-language works237,207