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Record W2489374928 · doi:10.5539/ies.v9n8p144

The Research on Strategies of College English Teachers Classroom Questioning

2016· article· en· W2489374928 on OpenAlexvenueno aff
Cao Wang-ru

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationClass (philosophy)PsychologyCompetence (human resources)Teaching methodPedagogySocratic questioningQuality (philosophy)Computer scienceSocial psychology

Abstract

fetched live from OpenAlex

<p class="apa">Questioning is one of the most frequently used strategies in classroom teaching, as well as the most influential teaching skill. It is a useful way for teachers to output information, to convey information and to obtain feedback from students. Teachers can also use it to communicate with their students. Effective questioning in class can encourage students to give relative and complete answers. It can activate students’ thought, develop their recognition and organize the class as well. However, there is little research in teachers’ questioning, especially in which teachers’ questioning and students’ expectations are combined. This study aims to explore the teachers’ questioning characteristics from the following aspects: the types of questions, the ways of answering questions, questioning strategies, the distribution of questions, wait time and feedback in college EFL class. The results may contribute to the teachers’ questioning and the second language acquisition in EFL classrooms; meanwhile it may train students’ language competence and improve the efficiency of teaching quality.</p>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

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

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 head0.188
GPT teacher head0.451
Teacher spread0.263 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations27
Published2016
Admission routes1
Has abstractyes

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