We don't learn from our mistakes: error-related arousal impairs subsequent memory formation
Bibliographic record
Abstract
Realizing that we’ve made an error triggers cognitive and behavioral adjustments, including increased arousal, attention, and more cautious responding (Jentzsch & Dudschig, 2009). These post-error adjustments are thought to boost task engagement and facilitate learning (Holroyd & Coles, 2002; Yeung, Botvinick, & Cohen, 2004). Yet, how errors affect memory encoding–a cognitive process foundational to learning–remains unknown. One possibility is that by increasing arousal and task engagement, errors would improve people’s ability to encode information that comes next. Alternatively, errors might lead to too much arousal and/or attentional capture, impairing people’s ability to encode information that comes next. In two experiments, we tested whether categorization errors influence how well people encode information presented after errors. In experiment 1, participants (n=60) categorized trial-unique images as ‘living’ or ‘nonliving’ and following a short delay, performed a surprise memory test. We found that people formed memories worse after categorization errors (p<0.001). In experiment 2, we investigated whether increases in arousal and/or attentional capture by errors contributed to post-error memory decrements in a separate cognitive control task. Participants (n=60) performed a modified Simon task in which they categorized trial-unique images as ‘natural’ or ‘man-made’, while we recorded pupil size and eye fixations and recognition memory for the images was later tested. Consistent with an arousal mechanism, individuals who displayed the largest increase in pupil size after errors had the greatest post-error memory decrements (p<0.05). Moreover, people with the largest post-error memory decrements tended to have better memory for the error trials and generated fewer fixations on post-error trials (ps<0.05) – consistent with the possibility that errors captured attention, leaving fewer encoding resources for information presented next. Our results suggest that rather than preparing people for learning opportunities, errors transiently impair memory encoding due to both increased arousal after errors and attentional capture by errors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".