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Data Collection: The Next Frontier |
| Sunday, November 10, 2013 |
| 9:00 AM–9:50 AM |
| Regency Ballroom D & E |
| Area: EDC; Domain: Conceptual/Theoretical |
| Instruction Level: Basic |
| CE Instructor: Joshua K. Pritchard, Ph.D. |
| Chair: Janet S. Twyman (UMass Medical School) |
| JOSHUA K. PRITCHARD (Florida Institute of Technology), RYAN LEE O'DONNELL (Florida Institute of Technology) |
 Dr. Joshua K. Pritchard is an assistant professor in applied behavior analysis at the Florida Institute of Technology. He received bachelor's and master's degrees from the Florida Institute of Technology. He earned his Ph.D. in behavior analysis from the University of Nevada, Reno. His professional experience includes providing direct consultation services for wide range of ages and populations in behavior acceleration and deceleration. Dr. Pritchard has served as a consultant with state facilities under review by the Department of Justice, done international consultation on behavioral programs and practicum experience, and conducted remote supervision of international students desiring certification in behavior analysis. Dr. Pritchard's research focuses on utilizing IRAP and Q Sort to examine complex human behavior, discovering and creating less expensive alternatives to traditional animal laboratories, transferring behavioral principles into marketable goods to improve quality of life and environmental behavior, and global dissemination of behavior analysis. |
 Ryan O'Donnell is a recent graduate of Florida Institute of Technology's applied behavior analysis master's program. As manager for JKP aquatic operant lab, Mr. O'Donnell oversees its care and implementation of several basic animal research experiments. Before attending Florida Tech, he received his bachelor's degree in psychology from the University of Nevada, Reno. His major interests are precision teaching, philosophical positions of the science of behavior, dissemination of behavior analysis, successful applications of technology to increase the efficiency of behavior analysts, and large-scale practical applications of behavioral technology. Mr. O'Donnell's thesis investigated a computer-based procedure to teach children to engage in the relational skills necessary for perspective-taking. He works as a Board Certified Behavior Analyst (BCBA) at Lodestone Academy, where he oversees the implementation of behavioral assessment and treatment to children diagnosed with a variety of disabilities in a school setting. Mr. O'Donnell has a diversity of experience gained during the past four years conducting behavioral assessments to then develop, implement, and train staff on behavior analytic programming. He has worked across several populations, including children and adults with developmental disabilities in outpatient, residential, and school settings. |
| Abstract: The ubiquity of handheld smart phones should be revolutionizing the data collection landscape of behavioral and educational professions. In fact, as platforms for user-developed applications grow, the creation of professional tools designed to increase efficiency and productivity in the workplace has exploded. Apps can increase efficiency from listing to-dos to typing reports. Fortunately, developers are beginning to create tools focused on the needs of a behavior analyst: data collection, delivery of instruction or therapy, and case management. Even with technologies that can greatly enhance the efficiency of these activities, a large proportion of analysts still are using tree- and graphite-based technologies. One potential problem with early adoption of smart-phone apps is that analysts have experienced effects opposite of those that were promised: They resulted in inefficiencies for the professional. Once bitten, twice shy--these professionals then become hesitant to abandon practices and tools which already work for those which may not. The purpose of this breakout is to kindle the appetite of its audience, provide a menu of the various options currently available, and break down the overwhelming and complex environment of smart-phone apps into accessible, bite-sized content. |
| Target Audience: Anyone interested in learning more about apps for behavior analysis data collection. |
| Learning Objectives: At the conclusion of the event, participants will be able to:
--Describe the benefits of using applications to increase efficiency in data collection.
--Identify which applications fit which contexts best.
-- Use the decision-tree, given a scenario, to determine an appropriate application to use.
--Identify one to three applications germane to their practice. |
| Keyword(s): apps, Data collection |
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