Split‐Attention and Coherence Principles in Multimedia Instruction Can Rescue Performance for Learners with Lower Working Memory Capacity
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
Summary This study examined the relation between working memory capacity (WMC) and the principles of Split‐Attention (Experiment 1) and Coherence (Experiment 2) in multimedia learning. Split‐Attention refers to reduced comprehension when learners must divide their attention between images and text, and Coherence refers to reduced comprehension when learners must process irrelevant information. In Experiment 1, those with lower WMC performed worse compared with those with higher WMC when learning from the Split‐Attention condition (audio + on‐screen text + images), but not when learning from the Complementary condition (audio + images). In Experiment 2, those with lower WMC performed worse compared with those with higher WMC when learning from the Incongruent condition (audio + irrelevant images), but not when learning from the Congruent condition (audio + relevant images). Findings reinforce the importance of pedagogically sound instructional design, as it may especially benefit those with lower WMC and equate learning across working memory abilities. Copyright © 2016 John Wiley & Sons, Ltd.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it