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Record W2028145550 · doi:10.5539/elt.v5n5p129

Studies and Suggestions on English Vocabulary Teaching and Learning

2012· article· en· W2028145550 on OpenAlexvenueno aff
Shigao Zheng

Bibliographic record

VenueEnglish Language Teaching · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyPsychologyVocabulary learningCompetence (human resources)Teaching methodCognitive styleLinguistic competenceMathematics educationVocabulary developmentCognitionLanguage acquisitionClass (philosophy)Learner autonomyAutonomyTask (project management)Language educationLinguisticsComputer scienceComprehension approachArtificial intelligence

Abstract

fetched live from OpenAlex

To improve vocabulary learning and teaching in ELT settings, two questionnaires are designed and directed to more than 100 students and teachers in one of China’s key universities. The findings suggest that an enhanced awareness of cultural difference, metaphorical competence, and learners’ autonomy in vocabulary acquisition will effectively facilitate the vocabulary learning. Simultaneously, a teaching model is recommended based on the findings of this survey, which incorporates ideas advocated by cognitive linguistics. Class instruction on vocabulary learning strategies can help students gain awareness of learning strategies. The greater the strategy awareness of learners, the more likely they will be to use task-appropriate learning strategies that help them overcome their general learning style limitations, and the more likely that these strategies will assist in processing, retrieving, and using new language information.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, 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 score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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

Citations22
Published2012
Admission routes1
Has abstractyes

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