47th Annual Convention; Online; 2021
All times listed are Eastern time (GMT-4 at the time of the convention in May).
|Alternating Treatments Designs: Interpretation Errors and Solutions|
|Sunday, May 30, 2021|
|4:00 PM–4:50 PM |
|Area: EDC; Domain: Basic Research|
|Chair: Robin Codding (Northeastern University)|
|CE Instructor: Robin Codding, Ph.D.|
|Presenting Author: CHRISTOPHER SKINNER (The Univesity of Tennessee)|
Alternating treatments designs can be used to evaluate multiple interventions and compare interventions. This presentation will address common interpretation errors that are associated with standard alternating treatments designs and propose solutions for each type of error. First, the presentation will focus on how researchers frequently conclude that an intervention or multiple interventions were effective, when changes may have been caused by uncontrolled threats to internal validity. A design solution to this problem, including a no-treatments series during the alternating treatments phase, will be described and analyzed. Next, the presentation will focus on misinterpretation associated with cumulative learning data. A proposed solution to this problem focus on supplementing repeated measures cumulative learning figures with figures that plot learning per session data. Discussion focuses on applied strengths of alternating treatments designs, effect size analysis, and how interpretation errors can adversely affect consumers of applied science.
|Instruction Level: Intermediate|
|Target Audience: |
researchers, graduate students, consumers of research
|Learning Objectives: At the conclusion of the presentation, participants will be able to: (1) identify similarities between A-B phase designs and standard alternating treatments design where both interventions are similarly effective; (2) employ a no-treatment control series during an alternating treatments phase can allow one to better control for threat to internal validity; (3) identify interpretation error associate with alternating treatment designs when cumulative learning is depicted on repeated measures graphs; (4) enhance their visual and effect size analysis by supplementing cumulative learning graphs with learning per sessions graphs.|
|CHRISTOPHER SKINNER (The Univesity of Tennessee)|
Christopher H. Skinner received his Ph.D. in School Psychology program from Lehigh University in 1989. While at Lehigh, he served as a special education teaching assistant for elementary students with Autism and as a teacher for 10th grade students with emotional/behavioral disorders. After finishing his Ph.D., Skinner was an assistant professor at The University of Alabama (3 years) and coordinator of School Psychology Programs at Mississippi State University (7 years) and The University of Tennessee (15 years). Currently, he is Professor at The University of Tennessee and teaches graduate courses in the School Psychology and Behavior Analysis programs. Skinner has co-authored over 200 peer-refereed journal articles and earned three national research awards including the Fred S. Keller Award for empirically validating interventions. Skinner’s accomplishments can be directly traced to his work with exceptional graduate students and practitioners. He is happiest when he is partnering with his students to work with educational professional to remedy presenting behavior or academic problems, while also conducting applied research. To simultaneously accomplish these goals, Skinner and his collaborators have relied single-subject design procedures.
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