Incidental Learning of Collocations in an Academic Lecture Through Different Input Modes
Bibliographic record
Abstract
Abstract In this quasi‐experimental study, 165 learners of English for academic purposes at a university in China were randomly assigned to five experimental groups and a control group. Each experimental group encountered 19 target collocations in the same academic lecture in one of the following input modes: (a) reading, (b) listening, (c) reading while listening, (d) viewing, and (e) viewing with captions. The control group did not receive any treatment. The results revealed that reading, viewing, and viewing with captions led to learning at the form recognition level, but no significant differences were found in the learning gains across these modes. Nonverbal elaboration, type of vocabulary, and type of verbal elaboration affected learning, but frequency of occurrence, strength of association, comprehension, and prior knowledge of general vocabulary did not. This study provides further evidence supporting the use of academic lectures for incidental learning of collocations as well as expanding on the multimedia learning theory.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".