The Development and Initial Validation of O-WSVLT, a Meaning-Recall Online L2 Spanish Vocabulary Levels Test
Why this work is in the frame
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Bibliographic record
Abstract
Recent literature in the field of L2 vocabulary assessment has advocated for the development of written receptive vocabulary tests such as Vocabulary Levels Tests (VLTs) that use: (a) meaning-recall item formats, (b) a minimum of 40 item counts per 1,000-frequency band to improve level estimates, and (c) lemmas (not word-families) as the lexical unit . With such recommendations in mind, this study presents the development and initial validation of Online written meaning-recall Spanish Vocabulary Levels Test (O-WSVLT), the first 120-item meaning-recall vocabulary levels test that measures knowledge of the 3,000 most frequent words in Spanish. A total of 209 L1-English learners of L2-Spanish participated in the study. Focusing on internal technical qualities of the test, Rasch measurement analysis was employed to provide evidence regarding four aspects of construct validity: content (i.e. representativeness and technical quality), substantive, structural, and generalizability . Results showed that (1) the items presented adequate spread of difficulty, (2) items demonstrated high levels of unidimensionality, and (3) O-WSVLT displayed an excellent fit to the Rasch model, with Rasch person and item reliability coefficients of 0.97 and 0.99 respectively. O-WVLT fills a gap by providing L2 Spanish teachers and researchers with a reliable tool to measure students’ written receptive meaning-recall vocabulary knowledge.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it