Measuring the iterative process of creative thinking: Uncovering the interplay between divergent and convergent thinking

Assessments of Creative Thinking often treat divergent and convergent thinking as separate processes, failing to capture their interaction within iterative problem-solving. The current study introduces an interactive task, ‘Structures’, designed to measure these cognitive processes in tandem. Participants ( N = 122) were tasked with designing polygons under constraints and received real-time feedback to refine their solutions. Measures of divergent and convergent thinking were automatically extracted from the variability of feature combinations in the attempted solutions and the consistency in the progress of these attempts. A model that combines both independent measures was best in explaining overall performance. Results also show a negative correlation between divergent and convergent thinking, suggesting a trade-off. Post-hoc analysis suggests a third competency, resource allocation, that oversees the interplay between these. This work highlights the complementary yet competing processes within iterative Creative Thinking and underscores the potential of digital environments to capture higher-order cognitive skills. This study provides insights into the iterative process of Creative Thinking, a competence increasingly recognized as essential in the 21st century. Our findings emphasize the importance of fostering both divergent and convergent thinking to enhance Creative Thinking, and their balance. We exemplify tracing these sub-skills as participants tackle a difficult challenge and provide a freely available online tool for examination at https://technion.link/miri/polygon/?timer=20&display_timer=on . • Introduces Structures , a task measuring Creative Thinking in the iterative and dynamic context of problem-solving. • Divergent thinking was estimated from attempted solution variability; convergent thinking from consistency of improvements. • Results show a negative correlation between divergent and convergent thinking, suggesting a trade-off. • Task performance was best explained by divergent and convergent Thinking plus resource allocation (38% variance). • Advances the measurement of skills as iterative processes within Next-Generation Assessments, contrasting static methods.