Assessing Self-Regulated Reasoning in a Dynamic Motivational Field: The EFEKT Method

Traditional cognitive assessments primarily evaluate static reasoning ability and often fail to capture adaptive self-regulation under changing performance conditions. This study introduces the EFEKT method, a dynamic computer-based assessment framework, and investigates whether behavioral trajectories can identify recurring patterns of self-regulation and adaptive decision-making. Participants freely selected task difficulty across sequential trials and continuously adjusted their behavior in response to performance feedback. Sequential task choices and performance outcomes were used to derive behavioral trajectories, and clustering analyses were conducted on data from 9,113 participants. Five behavioral profiles emerged, differing in ambition regulation, adaptation to feedback, performance stability, and success rates. The findings indicate that repeated interactions between difficulty selection, feedback processing, and behavioral adjustment give rise to identifiable patterns of self-regulated behavior that extend beyond static measures of cognitive performance. The EFEKT method offers an integrative framework for assessing adaptive performance with potential applications in personnel selection and safety-critical occupations.