Implicit Knowledge, Explicit Knowledge, and Achievement in Second Language (L2) Spanish.
Bibliographic record
Abstract
Implicit and explicit knowledge of the second language (L2) are two central constructs in the field of second language acquisition (SLA). In recent years, there has been a renewed interest in obtaining valid and reliable measures of L2 learners’ implicit and explicit knowledge (e.g., Bowles, 2011; R. Ellis, 2005). The purpose of the present study was to examine the nature of the knowledge representations developed by two groups of learners of Spanish as a L2 at different levels of proficiency. The results show that the two groups differed with respect to their implicit and explicit knowledge of Spanish and also regarding the relationship between measures of those representations and the measures of L2 achievement used with each group. Résumé Les connaissances implicites et explicites de la langue seconde (L2) sont deux concepts centraux dans le domaine de l'acquisition de la langue seconde (ALS). Les dernières années ont vu un regain d’intérêt pour la recherche de moyens valides et fiables de mesurer les connaissances implicites et explicites des apprenants de L2 (par exemple, Bowles, 2011; R. Ellis, 2005). Le but de la présente étude a été d'examiner la nature des représentations des connaissances développées par deux groupes d'apprenants de l'espagnol comme L2 à différents niveaux de compétence. Les résultats démontrent qu’il existe des différences marquées entre les deux groupes au niveau de leurs connaissances implicites et explicites de l'espagnol, et aussi en ce qui concerne la relation entre les mesures de ces représentations et les mesures de performance en L2 utilisés avec chaque groupe.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".