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Record W2623771212 · doi:10.5539/elt.v10n7p96

The Development of English Language Teaching Skills for Graduate Students through the Process of Learning by Doing

2017· article· en· W2623771212 on OpenAlexvenueno aff
Wannakarn Likitrattanaporn

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Assessment and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsBrainstormingMathematics educationPsychologyProcess (computing)Teaching methodEnglish for specific purposesQualitative researchLanguage educationTeaching and learning centerPedagogyComputer scienceSociology

Abstract

fetched live from OpenAlex

The purposes of this investigation were 1) to examine the findings of effectiveness of the process of learning by doing conducted with 5 linguistic graduate students at Srinakharinwirot University, Bangkok, Thailand 2) to develop the linguistic graduate students skill of designing English teaching materials and teaching English language and 3) to find out the efficient format of learning by doing used for training the student teachers skill of teaching English. The subjects of the study were 5 graduate students majoring in Linguistics at Srinakharinwirot University. This investigation is a qualitative research. The research instrument was a questionnaire designed to ask the students’ opinions towards learning by doing of constructing English teaching materials and teaching English language of their own and their friends. The qualitative data from brainstorming in a group discussion were taken into account. The results showed that the students get the benefits from the process of learning by doing. It can assist them to discover the knowledge of designing English teaching materials and English teaching skill by themselves. It is also found out that the efficient format for training teaching skill of the student teachers should integrate with the activity of brainstorming in a group discussion in every teaching-learning step i.e. from the preparation step when the principles and teching techniques of language teaching input of Audio Lingual Method, Cognitive Code Learning Theory and Communicative Language Teahing Approach were presented, during the step of adaping teaching materials and experimenting the practical teaching in school as well as after the students completed their self reflection and peer reflection.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.420
Teacher spread0.394 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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