Wednesday: April 29, 2026 @ 12pm – 1pm

Through the Looking Glass: Using Advanced Analytics and Artificial Intelligence to Predict ABA Outcomes and Improve Service Delivery

Description of Webinar:

Behavior scientists and practitioners collect an incredible amount of data on the environment-behavior relations specific to their topic of research or the services they deliver. As the field advances in sophistication and complexity, many opportunities exist to analyze more complicated and complex environment-behavioral relations. In this presentation, we discuss how the modeling repertoire present in many behavior scientists’ or practitioners’ repertoires can be extended to take advantage of more advanced analytic techniques (e.g., nonlinear time-series forecasting, machine learning) and how available tools make this increasingly easier to do. To make this tractable, this presentation also shows the utility of these analyses by using artificial intelligence (AI) to predict client outcomes in applied behavior analysis (ABA) service delivery settings, and how the resulting information can be used to improve ABA service delivery. In the current era of large data sets and AI, behavior scientists who learn to leverage these techniques will likely be able to ask questions and learn more about environment-behavior relations than historically possible.

Outcomes of Webinar:

Audience members will describe what unsupervised machine learning is and its utility in ABA settings.

Audience members will describe what supervised machine learning is and its utility in ABA settings.

Audience members will describe three use cases where artificial intelligence can help them learn new things about their clients.

Would you like to provide CEUs for the webinar?:
Yes

Presenter Bios:

Dr. David Cox can formally lay claim to being a bioethicist (master’s degree from Union Graduate College), a board-certified behavior analyst at the doctoral level (PhD in behavior analysis from the University of Florida), a behavioral economist (post-doc training at the Behavioral Pharmacology Research Unit at Johns Hopkins University School of Medicine), and a data scientist (post-doc training through an Insight! Data Science Fellowship). He has worked in behavior analysis for 20 years as a clinician, academic researcher, scholar, technologist, and all-around behavior science junky. From his work and collaborations, David has published over 70 peer-reviewed articles, book chapters, and books. And, has had the fortune to serve as Editor in Chief for The Experimental Analysis of Human Behavior Bulletin and Associate or Guest Editor for Perspectives on Behavior Science, Behavior Analysis in Practice, Journal of Applied Behavior Analysis, Psychological Record, Education and Treatment of Children, Toward Data Science, and Behavior and Social Issues. When he’s not doing research or building quantitative models of behavior-environment relations, he enjoys spending time with his wife, two beagles, and two kittens around St. John’s, FL.

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