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Record W1916138938 · doi:10.5539/elt.v8n11p69

A Study of Effect of Dramatic Activities on Improving English Communicative Speaking Skill of Grade 11th Students

2015· article· en· W1916138938 on OpenAlexvenueno aff
Prisana Iamsaard, Sakon Kerdpol

Bibliographic record

VenueEnglish Language Teaching · 2015
Typearticle
Languageen
FieldComputer Science
TopicEnglish Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyClass (philosophy)Communicative language teachingWorkforceTest (biology)PedagogyMathematics educationLanguage educationPolitical science

Abstract

fetched live from OpenAlex

This paper aimed to reexamine the current EFL communicative speaking skill in high school level in Thailand due to the coming of the entry to ASEAN at the end of the year 2015. Thai students need to be wellprepared for workforce in the future since English is used as the working language in ASEAN. The purposes of this paper were to study the effect of dramatic activities on improving English communicative skills of grade 11th participants and to examine students’ opinions towards the use of dramatic activities in their speaking class. The duration of experiment was 21 hours within 7 weeks. The research instruments were lesson plans using dramatic activities, English communicative speaking test and a questionnaire measuring students’ opinions towards the teaching based on dramatic activities. The findings were that the English communicative speaking skill on grade 11th students after attending the teaching class using dramatic activities was significantly higher than before attending the teaching and the students’ opinions towards dramatic activities on speaking were highly positive.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.300
Teacher spread0.287 · 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 designObservational
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

Citations23
Published2015
Admission routes1
Has abstractyes

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