Incidental Learning of L2 Collocations in an Academic Lecture: A Multimedia Theory Perspective
Bibliographic record
Abstract
This study aimed to examine how L1 Arabic learners incidentally acquire L2 English collocations through various input modes in academic lectures. A quasi-experimental design was employed, involving 87 Arabic learners studying L2 English at a Saudi university. The participants were randomly divided into six groups (5 intervention groups and one control group). An objective type multiple-choice question test was conducted in three phases: a pre-test, immediate post-test, and delayed post-test, to assess the participants' learning. Each experimental group received a specific input mode during the lecture, encountering a total of 17 English collocations. The input modes included listening, reading, reading while listening, viewing, and viewing with captions. The data were analyzed using SPSS version 25.0, employing ANOVA tests to compare mean scores across different test types (pre-test, immediate post-test, and delayed post-test) and the five input modes. The results revealed significant improvements in form-recognition learning from reading, viewing, and viewing with captions. These findings contribute further evidence supporting the effectiveness of academic lectures and multimedia theory in facilitating the incidental acquisition of L2 collocations.
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.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".