|
SQAB Panel: The Role of Computation in Behavior Science: A Panel and Audience Discussion |
Saturday, May 24, 2025 |
4:00 PM–4:50 PM |
Convention Center, Street Level, 140 A |
Area: PCH; Domain: Theory |
CE Instructor: Andrew Craig, Ph.D. |
Chair: Sarah Cowie (University of Auckland, New Zealand) |
Discussant: Suzanne H. Mitchell (Oregon Health & Science University) |
ANDREW R. CRAIG (SUNY Upstate Medical University) |
SHAWN PATRICK GILROY (Louisiana State University) |
SAMUEL MORRIS (Louisiana State University) |
 Andy Craig is an Associate Professor of Behavior Analysis Studies, Pediatrics, and Neuroscience and Physiology; Director for Research in the Golisano Center for Special Needs; and Chair of the Behavior Analysis Studies Department at SUNY Upstate Medical University. Andy is Associate Editor for the Journal of the Experimental Analysis of Behavior and Behavior Analysis: Research and Practice, and he is on the editorial boards for the Journal of Applied Behavior Analysis, Behavior Analysis in Practice, and Perspectives on Behavior Science. He has served ad hoc editorial and reviewer roles for several other journals that publish research in behavior analysis. He serves in leadership positions in Division 25 of the APA, the Society for the Quantitative Analyses of Behavior, and the Society for the Experimental Analysis of Behavior. Andy’s research focuses on topics broadly related to persistence, treatment maintenance, and stimulus generalization, and he approaches these questions from basic, translational, and applied angles. He is a recipient of the B. F. Skinner Foundation New Researcher Award from APA Division 25 and the Joseph V. Brady Significant Research Contribution Award from the Society for the Experimental Analysis of Behavior. |
 Dr. Shawn Gilroy is an assistant professor of psychology in the school psychology and behavior analysis programs at Louisiana State University. His work often features statistical analysis (i.e., both single-case and group design) as well as applications of methods derived from computer science (e.g., machine learning, reinforcement learning). This work includes meta-science applications (e.g., summarizing and characterizing treatment outcomes) as well as novel methods for characterizing reinforcer effects (e.g., reinforcement learning applied to evaluations of reinforcer efficacy). Dr. Gilroy has also been involved in developing various tools designed to guide behavior analysts in applying statistical and computational methods. |
 Sam Morris obtained his Ph.D. in Psychology with a specialization in Behavior Analysis at the University of Florida under the mentorship of Dr. Tim Vollmer. He was an Assistant Professor and the Applied Behavior Analysis Program Coordinator at Southeastern Louisiana University before beginning his current position as an Assistant Professor in the Department of Psychology at Louisiana State University in 2022. Dr. Morris' research interests span the basic-applied continuum. His laboratory utilizes experimental manipulations of the environment to investigate causal influences on choice and inform methods of facilitating behavior change. The individualization of reinforcement procedures and relative efficacy of different types and parameters of reinforcement have proven uniting themes underlying his research to date. Dr. Morris teaches a variety of behavior-analytic courses at the undergraduate and graduate level, serves on the editorial board for the Journal of Applied Behavior Analysis, and frequently serves as a reviewer for top behavior-analytic journals. |
Abstract: Panelists will offer diverse perspectives on the role of computation in designing, conducting, analyzing, and publishing behavior science with the goal of engaging the audience in related dialogue. Panelists will offer diverse perspectives on the role of computation in designing, conducting, analyzing, and publishing behavior science with the goal of engaging the audience in related dialogue. |
Instruction Level: Intermediate |
Target Audience: Board certified behavior analysts; licensed psychologists; graduate students. |
Learning Objectives: 1. describe computational approaches that are currently used in behavioral science 2. describe potential strengths of computational approaches in behavior science 3. describe potential weaknesses of computational approaches in behavior science |
|
|