Everyday Attention: Variation in Mind Wandering and Memory in a Lecture
Bibliographic record
Abstract
Summary Understanding the factors underlying variation in attentional state is critical in a number of domains. Here, we investigate the relation between time on task and mind wandering (i.e., a state of decoupled attention) in the context of a lecture. Lectures are the primary means of knowledge transmission in post secondary education rendering an understanding of attentional variations in lectures a pressing practical concern. We report two experiments wherein participants watched a video recorded lecture either alone (Experiment 1) or in a classroom context (Experiment 2). Participants responded to mind wandering probes at various times in the lecture in an effort to track variations in mind wandering over time. In addition, following the lecture, memory for the lecture material was tested. Results demonstrate that in a lecture mind wandering increases with time on task and memory for the lecture material decreases. In addition, there was a significant relation between mind wandering and memory for lecture material. Theoretical and practical applications of the present results are discussed. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.010 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 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".