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Record W2099886492 · doi:10.18806/tesl.v30i7.1157

Is It Rude Language? Children Learning Pragmatics Through Visual Narrative

2014· article· en· W2099886492 on OpenAlexvenueaboutno aff
Noriko Ishihara

Bibliographic record

VenueTESL Canada Journal · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsFormalityPragmaticsDialogicContext (archaeology)NarrativePsychologyRubricLinguisticsForeign languagePolitenessLanguage acquisitionLanguage educationPedagogyMathematics education

Abstract

fetched live from OpenAlex

There has been an upsurge of interest in teaching second/foreign language (L2) pragmatics in recent years, but much of this effort has been targeted at adult learners. This article introduces small-scale informal instruction exploring the pragmatic development of 9-year-olds in Tokyo, facilitated through dialogic in- tervention on pragmatics using the visual presentation of narratives. Although the instruction took place in an English as a foreign language (EFL) context, the same dialogic approach is relevant to ESL in Canada and elsewhere, as picture books enrich narratives, visually mediating the context of language use in a manner comprehensible and captivating to young learners. The learners’ pragmatic development was scaffolded dialogically through instructional materials doubling as teacher-based assessments, including formality judgment tasks, discourse completion tasks, and student-generated visual discourse completion tasks, assessed through predesigned rubrics and written reflections by the teacher. Video-recorded data showed that repeated visual assistance provided by the teacher and peers led to enhanced pragmatic awareness and metapragmatic judgments of the relative levels of formality and politeness of the target pragmatic formulas. However, with little L2 exposure, these learners were often unable to produce newly introduced expressions and failed to match the demands of the context with appropriate language choices during this isolated series of instructional events.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, 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 score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0360.000

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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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

Citations21
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueTESL Canada JournalSame topicEFL/ESL Teaching and LearningFrench-language works237,207