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| Graphical Practices in Behavior Analysis: Adverse Effects of Nonstandard Line Graphs |
| Wednesday, February 1, 2017 |
| 2:30 PM–3:20 PM |
| Miramar Ballroom |
| Area: AUT; Domain: Basic Research |
| Instruction Level: Basic |
| CE Instructor: Richard M. Kubina Jr., Ph.D. |
| Chair: Jonathan J. Tarbox (FirstSteps for Kids) |
| RICHARD M. KUBINA JR. (Pennsylvania State University) |
 Richard M. Kubina, Jr., has a bachelor's degree (psychology) from Youngstown State University and a masters and a doctoral degree (special education) from The Ohio State University. Dr. Kubina is a Professor of Special Education at The Pennsylvania State University and teaches courses on methods for teaching reading, informal assessment, behavior analysis, and single case design. Dr. Kubina conducts wide-ranging research in the area of applied behavior analysis and precision teaching. Dr. Kubina is a Board Certified Behavior Analyst, Doctoral level (BCBA-D) and serves on a number of editorial boards for behavioral and special education journals. He was the past editor of the Journal of Precision Teaching and Celeration. |
| Abstract: Few of us would attend a hospital where 85% of the doctors made a judgment error. Yet a recent study revealed an 85% error rate in graph construction for 4,313 graphs across 11 behavior journals. Another study showed that trend analysis in behavioral journals has widespread variability; qualifications of trends such as "rapidly" and "moderately increasing" expose the price of subjectively embraced by behavior analysts. The fundamental data-driven process involving line graphs occur within fieldwork, theses, dissertations, lectures, conference presentations, and journal articles. Therefore, the problems with rampant graph constructor error and subjective determinations of key analytical techniques such as trend analysis require a meaningful solution. The current presentation will share data and discuss how foundational assessment procedures involving line graphs can improve with standard ratio charts. |
| Target Audience: Certified behavior analysts, licensed psychologists, graduate students. |
| Learning Objectives: At the conclusion of the presentation, participants will be able to: (1)) describe the proportional construction rule for constructing a linear graph; (2) compare essential structure and quality features of linear graph construction; (3) define nonstandardization as it applies to linear graphs. |
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