Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


41st Annual Convention; San Antonio, TX; 2015

Event Details

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Symposium #211
CE Offered: BACB
Measurement in Behavior Analysis: From the Minds Eye to the SCC
Sunday, May 24, 2015
2:00 PM–3:50 PM
007C (CC)
Area: TPC/PRA; Domain: Service Delivery
Chair: Kristin Robinson (Saint Louis University)
Discussant: Henry S. Pennypacker (University of Florida)
CE Instructor: Ryan Lee O'Donnell, M.S.

Behavior analysis has a unique and difficult task in the measuring behavior. The ephemeral nature, range of topographies, and functional complexity of behavior poses a challenge mostly unknown to other natural sciences. Therefore, it is of little surprise that behavior measurement is accomplished using a wide range of measuring instruments, techniques, displays, and dimensions. Behavior analysis was fortunate to have been founded in conjunction with the most sophisticated technology every devised in the pursuit of behavior measurement, the cumulative recorder. However, from a practical standpoint there is important potential for scientists and practitioners in identifying the most effective and simple measurement system, and the ability to analyze data in the absence of numbers and machines. This presentation will cover the basic philosophical roots and techniques of behavior measurement, the machine-less flexibility of measuring with the minds eye, and a guide to selecting quick and easy measurement tools from the standpoint of a seasoned practitioner.

Keyword(s): Measurement, Mind's Eye, Precision Teaching, Standard Celeration
The Role of Measurement in Science
SCOTT A. MILLER (University of Nebraska Medical Center)
Abstract: The endeavors of scientists are inextricably linked to the measurement system they use. Measurement is the qualitative and quantitative categorization of events into arbitrary segments called “data.” Most events can be quantified using a wide variety of techniques. The nature of the technique employed in the quantification of events naturally sets the parameters for interpretability of those events. That is, how data is collected and analyzed directly affects the kind of interpretations that can be gleaned from those data. The art of quantitative and mathematical analysis, description, and visual display of data have continuously evolved and influenced scientists’ behaviors. In the narrative of scientific dissemination, the conflict is the motivation to produce meaningful−and simultaneously conservative data. Therefore, it may be tempting to select measuring systems that are likely to enhance the apparent robustness of an experiment. The scientific process may potentially be weakened by favoring superlative aesthetics over high quality and conservative data analysis. The purpose of this presentation is to discuss criteria and parameters when selecting a measurement system, and the influence of data on the behavior of the scientist.
Hear Ye, Hear Ye! What’s This Thing Called The SCC?
Abstract: What is the Standard Celeration Chart (SCC)? What are its conceptual origins? Isn’t it part of that cultish Precision Teaching movement? When should I use it? Am I missing anything if I never use it? If you have had brushes with the Standard Celeration Chart, you may have asked yourself some of these questions. Or you may be asking yourself “What’s this funky blue chart? Didn’t it get dropped from the big exam?!” This presentation will help to introduce the Standard Celeration Chart and clarify how it can be immediately beneficial in practice as well as why it is conceptually important and related to the history of the field of behavior analysis. In addition I will also point out when alternative graphical displays may be superior to the Standard Celeration Chart and how to decide which charting method to use given the current situation while staying true to our discipline’s pragmatic roots.
Measurement Gripes and Glows: Clinics, Classrooms, and Centers
AMY LYNN EVANS (Fluency Factory)
Abstract: A behavior analyst must not only choose appropriate measurement tools and techniques, but also help create data-friendly cultures in applied settings. To maximize effectiveness in this endeavor, one must consider the difficulties of influencing people to collect data accurately and emphasize the importance and utility of analyzing the data that they have been asked to collect. When measurement systems are ineffectively utilized or under-utilized, what factors underlie this lapse? Common complaints among teachers and behavior analysts about measurement (especially the Standard Celeration Chart [SCC]) are likely to be comprised of anecdotal reports as opposed to empirical evidence in accounting for the reasons measurement tools go under-utilized in certain settings. Conversely, it is worth examining the variables that underlie embracing the effective utilization of measurement. Key elements of successful implementation will be discussed. Finally, we will explore the role of setting and culture in the successful implementation of measurement systems. For example, how teachers, parents, and students analyze data differently, how does using the SCC affect the culture of an organization, who uses the SCC once there are no longer requirements to do so, and which components of a measurement system survive without the watchful eye of a behavior analyst or precision teacher, are questions that will be explored.

Mind's Eye Data: If You Aren't Taking Data You May Be Doing Behavior Analysis!


The mind has both historically and rightfully been waved off as a slippery slope that leads to dualistic views of behavior and practically invaluable psychological interpretations, technologies and systems. The old behavior analytic saying goes, "If you aren't taking data, then you aren't doing behavior analysis!" While this may be true under certain circumstances, it conflicts with various behaviorisms such as Skinner's radical behaviorism and functional contextualism. This presentation will begin with a short anecdote from a graduate student working late in the night while listening to behavior analytic podcasts in which Owen White suggested that we only take data when we think we may be wrong. I will suggest that there may be conditions under which the "mind's eye" is appropriate and valuable to a behavior analyst, as well as provide preliminary data on the possible conditions under which mind's eye data is a worthwhile venture for behavior analysts.




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