Keeners and Procrastinators: Investigating Individual differences in visual cognition between voluntary signup across school semesters
Bibliographic record
Abstract
University-based psychological research typically relies on the participation of undergraduate students for data collection. With such participants, circadian timing effects have been shown to modulate attention and cognitive control, with student participants showing greater attention control in the afternoon than in the morning (Blake, 1967). On a longer time scale, researchers have anecdotally commented that semester differences may produce different outcomes in attentional and cognitive studies, with participants that sign up early in the semester being more attentive and focussed than those that sign up at the end of the semester. The purpose of our study was to test this anecdotal claim, and investigate the effect of time of semester across a set of attentional and cognitive tasks. To do so, participants completed canonical versions of a visual working memory (VWM) task, a flanker task, and a multiple object tracking (MOT) task. Crucially, we tested students who signed up at the beginning of the semester (within the first 3 weeks of school), and at the end of the semester (within 3 weeks until the end of class). Our results demonstrate that students at the end of the semester did not show any significant differences in the MOT task and VWM task, even though both these tasks require high levels of effort and concentration. Interestingly, there was a significant difference in the flanker task, such that early semester students showed a stronger flanker effect. In other words, later semester students were less susceptible to inference from irrelevant peripheral distractors, suggesting differences in perceptual load across the early and later semester groups. Overall, it appears that there can be differences between participants who choose to sign up early in the semester from those near the end of the semester, but these differences may be limited to particular cognitive processes Meeting abstract presented at VSS 2015
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| 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 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".