Lexical Availability Output in L2 and L3 EFL Learners: Is There a Difference?
Bibliographic record
Abstract
English as a foreign language (EFL) is a global issue that extends to thousands of learners worldwide who share a similar classroom situation. However, researchers have often considered learners to have homogeneous linguistic profiles, overlooking the fact that EFL classrooms in primary and secondary education include learners with different linguistic profiles. Despite the fact that immigrant and non-immigrant students meet every day in classrooms, little is known about the EFL performance of the former compared to the latter. This paper addresses this reality, and explores the vocabulary performance of immigrant students, learners of English as an L3, compared to learners of English as an L2 who had the same course level and were from the same community. The research questions were twofold: (1) to ascertain whether there were quantitative differences between L2 and L3 English learners in terms of the number of words produced by each group, and (2) to ascertain whether there were qualitative differences in the words produced by the L3 and L2 groups with regard to (a) the most and least productive prompts for each group, and (b) the number of infrequent words appearing in the production of each group. The sample consisted of 14 bilingual students who were learners of English as an L3 and 14 monolingual learners of English as an L2, respectively, who were in the twelfth year of Spanish secondary education (age 17-18 years old). The data collection instrument was a lexical availability task consisting of six prompts. The data were lemmatized, coded and analysed by means of WordSmith Tools and the VocabProfile programme. The results indicated that the L2 group produced a greater number of words and a higher percentage of infrequent words in the most productive prompt.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".