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Record W4281654916 · doi:10.5430/wjel.v12n5p306

The Acquisition Order of Vocabulary Knowledge Aspects in Thai EFL Learners

2022· article· en· W4281654916 on OpenAlex
Apisak Sukying, Worakrit Nontasee

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyComputer scienceConstruct (python library)Test (biology)Vocabulary learningProcess (computing)PsychologyNatural language processingMathematics educationLinguistics

Abstract

fetched live from OpenAlex

The present study explored vocabulary knowledge as a multi-aspect construct by examining the acquisition order of different vocabulary aspects and the relationships between these aspects. A battery test of receptive and productive vocabulary aspects, based on Nation’s (2013) framework, was administered to 156 Thai EFL learners in tenth (n = 84) and twelfth (n = 72) grades. Two different grades of Thai EFL learners were used to better describe the vocabulary acquisition process. The results indicated that scores on the tests assessing receptive knowledge of an aspect were higher than scores on the productive knowledge tests, for both grades. However, overall, the twelfth-grade learners performed better than the tenth-grade learners. The findings also revealed significant correlations between knowledge of the different aspects. Furthermore, the Implicational Scaling (IS) analysis revealed that the two grades had distinct implicational patterns of vocabulary aspects. These results provide empirical evidence for the vocabulary acquisition pattern. The results also suggest that vocabulary knowledge is an incremental learning process and that exposure to vocabulary knowledge has positive effects on vocabulary acquisition.

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.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.218
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.000

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 head0.009
GPT teacher head0.289
Teacher spread0.279 · 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