The Acquisition Order of Vocabulary Knowledge Aspects in Thai EFL Learners
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".