Foundational work in the Quantitative Analysis of Behavior (QAB) has shaped our conceptualization of behavioral processes and provided insightful ways to describe order in our data.  More recently, researchers have begun applying these insights and quantitative approaches to issues of societal importance.  Examples of this Applied Quantitative Analysis of Behavior (A-QAB) include the use of behavioral economics to understand health behavior, the use of quantitative models to highlight mechanisms of drug action, leveraging the insights of QAB approaches to describe the resurgence of problem behavior in clinical populations, and more.

We invite the submission of scholarly work providing discussion, examples, technical papers, or summaries of these efforts for a special section of Perspectives on Behavior Science on A-QAB.

Submission Deadline: January 1, 2021 
Guest Editors: David Jarmolowicz, Peter Killeen, Sally Huskinson, Brian Greer

The purpose of this special section is to provide an outlet for quantitative researchers to explain the possible applications and implications of using various advanced quantitative techniques to SCED data through Perspectives on Behavior Science. Manuscripts that provide guidelines and/or step-by-step procedures with applied examples for SCED researchers are strongly preferred. We also invite applied behavior analysts (e.g., clinical behavior analytic scientists) to provide a commentary on the next steps needed to expand the application of advanced quantitative techniques to SCED data.

Submission Deadline: November 1, 2020

Guest Editors: Lucy Barnard-Brak, David M. Richman, Laci Watkins

As a result of the significant disruption that is being caused by the COVID-19 pandemic, we are very aware that many researchers will have difficulty in adhering to the normal timelines associated with many steps of the publication process, including peer review.  Please do let us know if you need additional time at any step. Our systems will continue to remind you of the original timelines, but we intend to be highly flexible at this time.

Direct Instruction (DI) is a powerful teaching system that combines logical selection and sequencing of examples and high rates of student responding to mastery. Countless children and adults owe their literacy and early academic success to teachers who skillfully presented DI programs developed by Siegfried Engelmann and colleagues. In acknowledgement of the central importance of this topic to behavior analysis, science, and learning, Perspectives on Behavior Science and Behavior Analysis in Practice are planning special sections on Direct Instruction and the Science and Practice of Behavior Analysis.

Submission Deadline: September 1, 2020
POBS Guest Editors: William Heward and Janet Twyman