Date: March 30, 2022
Length: 60 minutes
Course Type: Archived Event
Instructors: Peter Pirolli, PhD
Learning Level: Fundamental
Primary Audience: PIs, Research coordinators, Postdoctoral researchers, Graduate students, Other study team members
Skills Domain: Data Management and Informatics, Scientific Concepts and Research Design
Investigate two threads of research on computational cognitive models of behavior change.
The March seminar of the Center for Quantitative Methods and Data Sciences (QM&DS), in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center at Tufts CTSI and the Data-Intensive Studies Center (DISC) at Tufts University, occurred on Wednesday, March 23, 2-3:00pm via Zoom. The topic of this webinar was "Computational Cognitive Models of Behavior Change in the Real World and at Scale"
Psychology calls itself the science of behavior, but some have lamented that “cognitive psychology [has] never had much to say about the meaningful activities people perform in their daily lives, nor have they really intended to.” In this presentation, Dr. Pirolli discusses two threads of research on computational cognitive models of human behavior change in the ecology of everyday life. The first thread of research concerns models of health behavior change occurring in multi-week, in-the-world, experiments using mobile health applications designed to promote physical activity, stress reduction, and improved nutrition habits. These computational models, built in the ACT-R cognitive architecture, provide an integrated account of goal intentions, implementation intentions, self-efficacy, motivation, self-affirmation, and habit strengthening underlying more than a half dozen behavior change techniques. The second thread of research expands on ACT-R models of behavior change to address how humans responded to the COVID-19 pandemic. Heterogeneous behavioral responses over time and geographical regions depend on the individual beliefs and information consumption patterns of populations. To address the need for more precise and accurate epidemiological models, we are researching Psychologically Valid Agent models of human responses to epidemic information and non-pharmaceutical interventions during the pandemic.
About the instructor:
Dr. Pirolli is currently a Senior Research Scientist at the Institute for Human and Machine Cognition. His research involves a mix of cognitive science, artificial intelligence, and human-computer interaction, with applications in digital health, sensemaking, and information foraging, among other things. Previously, Dr. Pirolli was at the Palo Alto Reseach Center, and was a Professor in the School of Education at UC Berkeley. He received his doctorate in cognitive psychology from Carnegie Mellon University in 1985. Dr. Pirolli received a B.Sc. in psychology and anthropology from Trent University. He has been elected as a Fellow of the National Academy of Inventors, the American Association for the Advancement of Science, the American Psychological Association (Div 3 and Div 21), the Association for Psychological Science, the National Academy of Education, and the ACM Computer-Human Interaction Academy. Please see his book titled “Information Foraging Theory: Adaptive Interaction with Information.”