The Impact of Real World Stressors on Problem-Solving

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This project examines how variability in daily stress and fatigue--previously dismissed as uncontrollable 'noise' in cognitive processing--relates to variability in learning and problem-solving. This project is motivated in part by evidence that performance on tests of executive function and memory can fluctuate as a function of recently experienced, real-world, daily stressors. Because problem-solving recruits these and other cognitive abilities, it is hypothesized that day-to-day stressors can also impact our approaches to and success with complex, open-ended challenges regularly faced in educational and professional contexts. Further, on the basis of preliminary research, it is anticipated that a subset of individuals will exhibit greater resilience to stressors than others. In other words, for some, day-to-day stressors may create contexts that facilitate tackling problems to greater or lesser degrees, whereas for others, recent stressors may impact outcomes minimally. This work wields important implications for STEM education given the increasing priority placed on problem-solving skills. It will offer new foundations for modeling individual differences in resilience and vulnerability to everyday stressors during complex tasks. Moreover, understanding stressor-related intra-individual variability can lead to strategies for improving performance of high-stakes, resource demanding operations (e.g., piloting an airplane). Building from methods of Ecological Momentary Assessment (EMA), both subjective and physiological measures of stress and fatigue will be sampled from healthy adults on a daily basis as they engage in their regular routines of daily life. These data will be uploaded by participants to a secure server via smart phone and will be monitored by research staff. When daily sampling logs suggest the recent experience of high, medium, or low levels of stressors, participants will be scheduled for a testing session to be conducted in their own home or at the research facilities of the Swartz Center for Computational Neuroscience. They will engage in STEM-related problem-solving tasks modeled after real world activities. Simultaneously, electroencephalographic (EEG) data, eye movement, and electrocardiography will be recorded and synchronized. Monitoring periods are expected to last between one and three months and encompass nine testing sessions. This project will result in a rich corpus of data that can be probed from many different angles, offering an unprecedented view of intra-individual variability in task performance as a function of day-to-day changes in physiological and cognitive state. It is expected to reveal behavioral and brain dynamics supporting insight and discovery. Further, expanding from episode-based models of the metacognitive components of problem-solving, it is expected to tease apart ways in which various theorized components--such as representing the problem space, exploring, planning a solution, and implementation--may be differently affected by daily stressors. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).