Focusing on eigendynamic effects promotes students’ performance in complex problem solving: A log-file analysis of strategic behavior

Abstract

Human beings are frequently confronted with complex systems that change dynamically over time. Correspondingly, so called eigendynamic effects are an important feature in complex problem solving (CPS) tasks. Eigendynamic effects describe increases or decreases in outcome variables over time without the individual's intervention. Identifying the eigendynamic effects from the start while exploring the system is reasonably an effective strategic behavior when systems are comprised of different effect types (i.e., eigendynamic effects alongside other effects). In this study, we hypothesized that the strategic behavior to identify eigendynamic effects early when exploring the system was related to CPS performance and mediated the relationship between intelligence and CPS performance. In a sample of N = 262 German high school students, the investigated strategic behavior predicted CPS performance when exploring the system (knowledge acquisition phase) and when controlling the system (knowledge application phase) in single CPS tasks and in a set of CPS tasks comprising of different effect types. In mediation models the strategic behavior to identify eigendynamic effects early mediated the intelligence-CPS performance relation in the knowledge acquisition phase, but not in the knowledge application phase. We discuss these findings in the light of how students interact with complex and dynamic systems, pointing to the importance of this strategic behavior for the relationship between intelligence and CPS.