MétaCan
Menu
Back to cohort
Record W2055189139 · doi:10.5539/elt.v8n3p35

Problematic Approach to English Learning and Teaching: A Case in Indonesia

2015· article· en· W2055189139 on OpenAlexvenueno aff
Himpun Panggabean

Bibliographic record

VenueEnglish Language Teaching · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsIndonesianCurriculumSubject (documents)AllotmentGrammarEnglish grammarPsychologyMathematics educationProcess (computing)LinguisticsTeaching methodPedagogyComputer science

Abstract

fetched live from OpenAlex

This article deals with problematic approach to English learning and teaching due to misleading conception on the nature of English and on the process of acquiring it as well as the clues to the issues. The clues are: Firstly, English is not more difficult than any other languages, including Indonesian language, Bahasa Indonesia (Note 1). Secondly, there are two approaches that need considering in English instruction, grammar free and strict grammar approaches. The former is highly recommended for early age instruction and beginners whereas the latter is recommended for instruction for specific purposes. However the two approaches should collaborate and their applications should be based on needs analysis. Thirdly, Conflicting conception on whether L1 and L2 are the same processes should not deter the strategy of how language is acquired naturally. When proper conception on the nature of English is attained and it is approached properly, English subject is not burdensome and needs not be eliminated from Primary School curriculum, and there is no need to reduce time allotment for the subject in Senior High School as stipulated in Indonesian English curriculum amendment.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.025
GPT teacher head0.260
Teacher spread0.235 · 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 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

Citations37
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicEFL/ESL Teaching and LearningFrench-language works237,207