Response Variability and Stability in Human Reasoning
Understanding how humans reason -- and how reasoning responses vary across tasks and individuals -- remains a core challenge for modeling and explanation in cognitive science. We investigate the stability of response patterns within reasoners and whether variation in these patterns can be used to predict learning effects. We introduce a formal, geometry-based method to quantify distances between individual reasoning patterns and their internal variability, grounded in heuristic theories. The proposed framework is tested against experimental data via generalized linear mixed-effects models and clustering, where we find that our proposed variation measure interacts with correctness to predi...
| Authors | Clemens Bombach, Rajmadan Lakshmanan, Marco Ragni |
|---|---|
| Primary category | cs.LO |
| Published | 2 October 2026 |
| Last updated at source | 2 October 2026 |
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