Vocabulary Learning through Extensive Reading: A Case Study.
Bibliographic record
Abstract
Abstract The role and importance of reading in second language vocabulary learning have been discussed by many researchers because of the richness and variety of vocabulary in written texts compared to oral discourse (Horst, 2005; Nation, 2001). However, despite the recent increase of studies in this field, there are very few studies focusing on non-Western languages, including Japanese, compared to Indo-European languages. To fill the gap, this study explored the process of Japanese vocabulary acquisition through extensive reading. Data were collected through a pretest, eight immediate tests, a posttest, and a semistructured interview. The results indicate that extensive reading is especially beneficial in consolidating learners’ vocabulary knowledge and in encouraging learners to reflect on their interests and needs in vocabulary learning. Résumé Le rôle et l’importance de la lecture dans l’apprentissage du vocabulaire en langue seconde sont sujets de discussion pour de nombreux chercheurs en raison de la richesse et de la variété de la langue écrite en comparaison au discours oral (Horst, 2005 ; Nation, 2001). Toutefois, malgré la récente hausse d’études effectuées dans ce domaine, très peu d’études se concentrent sur les langues non-occidentales, incluant le japonais, en comparaison aux langues indo-européennes. Pour combler cette lacune, cette étude a exploré le processus d’acquisition du vocabulaire en japonais par la lecture assidue. Les données ont été recueillies grâce à un pré-test, huit tests immédiats, un post-test et une entrevue semi-structurée. Les résultats indiquent que la lecture assidue est particulièrement bénéfique pour la consolidation du vocabulaire des apprenants et pour encourager les apprenants à réfléchir à leurs intérêts et à leurs besoins dans l’apprentissage du vocabulaire.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".