Efficacy of Multimodal Glossing on Second Language Vocabulary Learning: A Meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This meta‐analysis examined the effectiveness of an additional gloss mode in single versus dual and dual versus triple glossing on second language (L2) learners’ word learning. In total, 22 studies, providing 26 independent effect sizes, were coded, and 11 moderator variables including quality of data sample, learner variables, gloss features, text features, and methodological features were examined. The results show that the overall effect of an additional gloss mode was medium ( g = 0.46) for immediate posttests and small ( g = 0.28) for delayed posttests. However, analyses of moderator variables indicated that the effect of additional gloss modes is influenced by a range of variables related to learner (e.g., proficiency), gloss (e.g., language), text (e.g., narrative vs. expository), and research design (e.g., test format). Importantly, adding an additional mode to single textual gloss enhances vocabulary learning, whereas adding a mode to dual glossing does not result in significantly better vocabulary learning. The findings suggest that using more than two gloss modes is not necessary because it does not always lead to better learning of new words.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.142 | 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 it