A Receptive Vocabulary Knowledge Test for French L2 Learners \nWith Academic Reading Goals
Bibliographic record
Abstract
Recent studies in second language acquisition have confirmed a positive correlation between L2 learners' lexical knowledge and their language abilities. In more specific terms, researchers are increasingly confirming the idea that vocabulary size greatly impacts reading comprehension. In order to estimate English L2 learners' vocabulary size, several kinds of receptive vocabulary tests have been developed. But what about French L2 learners? How is their vocabulary size measured? There appear to be few well designed measures available. This study describes the development and validation of a new measure for French, the Test de la taille du vocabulaire (TTV). The TTV is closely modeled on Nation's (1990) widely used Vocabulary Levels Test (VLT) and follows the guidelines written by Schmitt, Schmitt and Clapham (2001). The TTV draws on recent corpus-based frequency lists for French (Baudot, 1992; Lonsdale & Le Bras, 2009). Initially, a pilot version was trialled with 63 participants, then an improved version was administered to 175 participants at four levels of proficiency. Results attest to the TTV's validity: scores indicate that the higher the group, the larger its vocabulary size. Moreover, the mean scores across the four word sections decrease as the test sections became more difficult. This assessment tool also proved to be reliable as performance on the test confirmed learners' level as determined by the institutional placement test. Post-test interviews with the participants confirmed their knowledge of the test words. Recommendations for improving the TTV, implications for theory and practice, and limitations will be discussed.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".