How Effective Are Intentional Vocabulary‐Learning Activities? A Meta‐Analysis
Bibliographic record
Abstract
Abstract The present meta‐analysis aimed to summarize the extent to which second language vocabulary is learned from the most frequently researched word‐focused activities: flashcards, word lists, writing, and fill‐in‐the‐blanks. One hundred effect sizes from 22 studies were included in meta‐regression analyses and administered separately for the observations measured with meaning‐recall and form‐recall tests. The results revealed that the average percentage learning gains were 60.1% and 58.5% on meaning‐recall and form‐recall immediate posttests. These gains dropped to 39.4% and 25.1% on delayed meaning‐ and form‐recall tests, respectively. These results suggest that learning through word‐focused tasks is far from guaranteed. Moreover, the percentage learning gains among the different activities ranged from 18.4% to 77.0% on immediate posttests and from 23.9% to 73.4% on delayed posttests indicating that there is much variation in efficacy among the activities. Moderator analyses revealed that learners’ place of study and direction of learning affected learning.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".