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Collaborative problem solving (CPS) assessment is a new academic research field with a number of educational implications. In 2015, the Programme for International Student Assessment (PISA) assessed CPS with a computer‐simulated human‐agent (H‐A) approach that claimed to measure 12 individual CPS skills for the first time. After reviewing the approach, we conceptually embedded a computer‐based collaborative behavior assessment (COLBAS) into the overarching PISA 2015 CPS approach. COLBAS is an H‐A CPS assessment instrument that can be used to measure certain aspects of CPS. In addition, we applied a model‐based cluster analysis to the embedded COLBAS aspects. The analysis revealed three types of student collaborator profiles that differed in cognitive performance and motivation: (a) passive low‐performing (non‐)collaborators, (b) active high‐performing collaborators, and (c) compensating collaborators.

Collaborative problem solving (CPS) is an essential 21st century skill at the intersection of social collaboration and cognitive problem solving, and is increasingly integrated in educational programs, such as the influential Programme for International Student Assessment (PISA). As research has identified the impact of the Big Five personality traits either on cognitive ability or social collaboration skills in groups, this study firstly identified their impact on the conjoint construct of CPS. Results from structural equation modelling (N = 483) found openness to experience and agreeableness as predictors for CPS performance. The results are embedded in the lifelong learning and investment model by Ackermann and provide implications for PISA 2015, as original PISA 2015 CPS tasks were used.