The Effect of Auditory Input on Multimodal Reading Comprehension: An Examination of Adult Readers’ Eye Movements
Bibliographic record
Abstract
Abstract Comprehension of many types of texts involves constructing meaning from text and pictures. However, research examining how second language (L2) learners process text and pictures and the relationship with comprehension is scarce. Thus, while verbal input is often presented in written and auditory modes simultaneously (i.e., audio of text with simultaneous reading of it), we do not know how the auditory input affects L2 adult learners’ processing of text and pictures and its relation to comprehension. In the current study, L2 adult learners and native (L1) adults read and read while listening to an illustrated story while their eye movements were recorded. Immediately after reading, they completed a comprehension test. Results showed that the presence of auditory input allowed learners to spend more time looking at pictures and supported a better integration of text and pictures. No differences were observed between L2 and L1 readers’ allocation of attention to text and pictures. Both reading conditions led to similar levels of comprehension. Processing time on the text was positively related to comprehension for L2 readers, while it was associated to lower comprehension for L1 readers. Processing time on images was positively related to comprehension only for L1 readers.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".