Metacognitive Judgments, Study-Time Allocation and Inferences: The Effect of Multimedia Discrepancies.
Bibliographic record
Abstract
This study investigated undergraduate students' metacognitive judgments while learning about complex science topics using multimedia material (text and graph).A within-subjects design was used to examine the effect of discrepancies on study-time allocation, metacognative judgments and inference generation.There were three types of discrepancies: none, text (between two ideas in the text) and text and graph (between the text and graph).Forty (N=40) participants completed 12 trials where they were asked to provide 6 judgments: Ease of Learning judgments (EOLs), immediate and delayed Judgments of Learning (JOLs) for both text and graph and Retrospective Confidence Judgments (RCJs).Participants provided significantly lower JOLs for content that contained discrepancies but RCJs remained high across conditions.Discrepancies did not influence study-time allocation, but did significantly influence inference scores.Overall, results suggest that participants may be aware of discrepancies, but lack the control strategies needed to overcome them.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".