فراتر از عقل: مسیرهای پیچیدگی و یادگیری در ماتریس های پیشرفته ران به فرآیندهای خودگردانی و نظم های متقابل بستگی دارند

The Raven's Progressive Matrices (RPM) test entails a 40-min contextualized interaction with a set of progressively difficult cognitive activities. Item-to-item experiences accumulate to total scores determined by, and reflective of, cognitive abilities. The current research is interested in what happens during those 40 min. Personality (Openness, Extraversion and Neuroticism) and metacognitive factors have consistently been associated, albeit at low levels, with performance. 252 industry managers completed, inter alia, the RPM either with or without confidence ratings. Using multi-level modeling and controlling for general ability, we investigate whether a) experiential factors emerge in individual performance trajectories, b) whether trajectories are associated with cognitive and personality factors, and c) whether requirements to externalize metacognitive reflection (provide confidence ratings) links to performance. Results suggest that metacognitive reflection impeded performance; that learning trajectories are separable from performance trajectories; and that trajectories are statistically moderated, most notably by Neuroticism, over and above cognitive ability. Modeling item-level responses following experimental manipulations that serve as a catalyst for modifying cognition-personality relations, provides an important avenue for integrating experimental and differential methods. Psychometric complexity (ψC) and psychometric learning (ψL) are proposed as theoretically derived empirical bases to ground investigations of statistical moderation. Together they may provide a bridge to causal accounts of the divide between intelligence and personality.