MétaCan
Menu
Back to cohort
Record W2999128773 · doi:10.5539/elt.v13n2p86

Revisiting the Explicit Learning of Vocabulary of Chinese EFL Learners

2020· article· en· W2999128773 on OpenAlexvenueno aff
Chen Wang, Jingjing Yang

Bibliographic record

VenueEnglish Language Teaching · 2020
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyVocabularyAssociation (psychology)Meaning (existential)LinguisticsVocabulary learningVocabulary developmentCollocation (remote sensing)Teaching methodMathematics educationCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

This study intends to find out how the retention of new vocabulary items could be affected by the item type (collocations versus single words), association strength between collocates and the collocate-node relationship. 101 Chinese EFL learners encountered the new items in paired-associate format. Participants were assigned to three groups: learning two types of collocations with high association strength, learning two types of collocations with low association strength, and learning new items in single words. The results show that learning new items in collocations yielded better retention of receptive and productive knowledge of meaning than in single words. Collocations with greater association strength also led to better retention of meaning. Different item types and associate strength has little effect on the retention of form.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.012
GPT teacher head0.295
Teacher spread0.282 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicSecond Language Acquisition and LearningFrench-language works237,207