The Impact of Emotion on Learners’ Application of Basic Science Principles to Novel Problems
Bibliographic record
Abstract
PURPOSE: Training to become a physician is an emotionally laden experience. Research in cognitive psychology indicates that emotions can influence learning and performance, but the materials used in such research (e.g., word lists) rarely reflect the complexity of material presented in medical school. The present study examined whether emotions influence learning of basic science principles. METHOD: Fifty-five undergraduate psychology students were randomly assigned to write about positive, negative, or neutral life events for nine minutes. Participants were then taught three physiological concepts, each in the context of a single organ system. Testing consisted of 13 clinical cases, 7 presented with the same concept/organ system pairing used during training ("near transfer") and 6 with novel pairings ("far transfer"). Testing was repeated after one week with 13 additional cases. RESULTS: Forty-nine students provided complete data. Higher test scores were found when the concept/organ system pairing was held constant (near transfer = 51% correct vs. far = 33%; P < .001). Emotion condition influenced participants' overall performance, with individuals in the neutral condition (50.1%) performing better than those in the positive (38.2%, P < .05) and negative (37.7%, P < .001) emotion conditions. CONCLUSIONS: These data suggest that regardless of whether the emotion is positive or negative, mild affective states can impair learning of basic science concepts by novices. Demands on working memory and subsequent cognitive load provide a potential explanation. Future work will examine the extent to which these findings generalize to medical trainees.
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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 | 0.001 | 0.012 |
| 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 | 0.001 |
| 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 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".