The Effects of Sentence Writing on Second Language French and Korean Lexical Retention
Bibliographic record
Abstract
Abstract: This study investigates the effects of sentence writing (SW) on second language (L2) lexical retention by comparing two word-learning conditions: writing new words in sentences and repeated word-picture viewing. L2 learners of French and Korean attempted to learn 24 new words: 12 words with one condition and 12 words with another condition. Dependent measures were one immediate and two delayed posttests that required participants to produce target word forms. Results for both language groups revealed negative effects for SW, suggesting that SW can impede word-form learning during the initial stages of L2 vocabulary learning. Furthermore, the finding that the Korean learners' scores were much lower than the French learners' scores under the SW condition suggests that SW may result in even less retention when the L2 script is far more distant from one's first language (L1), thereby supporting the impact of L1–L2 orthographic distance on L2 word learning and retention.
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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 | 0.005 |
| 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) | 0.003 | 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".