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Record W4298145382 · doi:10.5430/wjel.v12n8p74

The Effect of Pragmatic Instruction on Developing Learners’ Use of Request Modifiers in the EFL Context

2022· article· en· W4298145382 on OpenAlexvenueno aff
Mia Huimin Chen, Shelly Xueting Ye, Jingxin He, Don Dong Yao

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceCompetence (human resources)PerceptionMathematics educationPreferencePsychology

Abstract

fetched live from OpenAlex

The aim of this study is to evaluate the effects of three teaching approaches: a deductive teaching approach, an inductive teaching approach, and an inductive-deductive teaching approach on facilitating Chinese EFL learners’ use of request modifiers. Written discourse completion tasks were employed to collect learners’ request data and a follow-up interview reported Chinese EFL learners’ overall positive attitudes towards pragmatic instruction with a preference for the deductive approach. The findings presented the necessity for instructions of request in EFL contexts and reveal the superiority of the inductive-deductive teaching approach on pragmatic knowledge. Combing the results of the experiment with learners’ perceptions, it indicates that practitioners should consider incorporating both deductive and inductive instructions to fit learners’ preferences of instructional styles and learning needs. Besides, in terms of learners’ pragmatic competence, such a teaching approach would also guarantee the treatment effect in both short and long runs.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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