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.

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47th Annual Convention; Online; 2021

All times listed are Eastern time (GMT-4 at the time of the convention in May).

Event Details

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Symposium #423
CE Offered: BACB
Teaching Graphing: A Discussion of the Past and Present With Suggestions for the Future
Monday, May 31, 2021
12:00 PM–12:50 PM
Online
Area: TBA; Domain: Translational
Chair: Kelsey Dachman (University of Kansas)
CE Instructor: Kelsey Dachman, Ph.D.
Abstract:

Graphing and visual analysis are essential to research and practice within applied behavioral science. Research investigating behavioral approaches to teaching graphing were first initiated in the late 1990s, however more recently there has been increased interest in and publication of such work. The presentations comprising this symposium will (a) provide a systematic review of the behavioral literature examining methods of, as well as tutorials for, teaching graphing across various platforms, (b) put forth data documenting the effectiveness and efficiency of enhanced written instructions for teaching graphing, and (c) show further data supporting the use of enhanced written instructions for teaching graphing, as well as advocating for the integration of choice methodology within research on and tutorials for teaching graphing. Suggested future directions for advancing research and practice related to teaching graphing will be discussed.

Instruction Level: Intermediate
Target Audience:

Prerequisites include familiarity with behavior analytic terminology and single-case research design methodology.

Learning Objectives: At the conclusion of the presentation, participants will be able to: (1) summarize the literature on teaching graphing of single-case research designs; (2) describe methods for using enhanced written instructions to teach graphing; and (3) discuss future directions for research on teaching graphing.
 
A Systematic Review of the Literature on Teaching Graphing: Trends and Their Implications
(Theory)
MARCELLA HANGEN (Drake University), REBECCA WOOLBERT (University of Kansas), Pamela L. Neidert (The University of Kansas), Robin Kuhn (University of Kansas)
Abstract: Since the start of behavior analysis, graphing has been a core feature of the field. While data ultimately guide research and treatment interventions, a subsequent graphical display allows for easy interpretation of data. Analysis of graphical display is imperative for determining functional relations and understanding behavioral processes. The purpose of this systematic review was to identify literature within the field of behavior analysis pertaining to teaching graphing, including both training materials and experimental research. The review documented important trends across publications and years, such as (a) the recent increasing trend in the publication of studies on teaching graphing, (b) the observation that graphing is successfully taught using a variety of procedures across various graphing platforms, and (c) to date, emphasis has been placed on teaching publication-quality graphs to individuals within academia. A summary and synthesis of published teaching materials and experimental studies on teaching individuals to graph will be presented in graphical form and discussed in the context of future directions for research and practice.
 
Real-Time Data to Evaluate Enhanced Written Instructions for Creating Publication-Quality Single-Case Design Graphs in Excel
(Applied Research)
KELSEY DACHMAN (University of Kansas), ALEC M BERNSTEIN (Marcus Autism Center, Children’s Healthcare of Atlanta; Department of Pediatrics, Emory University School of Medicine), Ashley Romero (University of Kansas), Pamela L. Neidert (The University of Kansas)
Abstract: Graphically depicting single-subject data is foundational in the science of behavior. Although there are several tutorials for graphing, especially in the ubiquitous Microsoft Excel, few have been empirically validated. Studies providing data supporting the effects of graphing tutorials often measure graphing accuracy as a permanent product. With several ways to create graphs in Excel, permanent product recording is limited in that one cannot identify if the participant followed the tutorial steps as written, and, thus, the true validity of the tutorial is still in question. Furthermore, few studies have reported assessment of maintenance and generalization. We first sought to consolidate the existing literature on graphing in Excel by creating enhanced written instructions (EWI). We then compared graphing accuracy as a permanent product and in real-time for seven participants within a multiple baseline design to validate the EWI directly. Additionally, due to COVID-19, we were able to assess the effects of the EWI presented in-vivo and virtually. Overall, EWI resulted in immediate, robust effects, which maintained and generalized across presentation formats. We discuss results relative to measurement procedures for validating staff trainings and the effectiveness of EWI for training graphing in-vivo and virtually.
 

Teaching Graphing Using Enhanced Written Instructions: Does Chunk Size Matter?

(Applied Research)
ASHLEY ROMERO (University of Kansas), REBECCA WOOLBERT (University of Kansas), Jeanne M. Donaldson (Louisiana State University), Pamela L. Neidert (The University of Kansas), Robin Kuhn (University of Kansas)
Abstract:

Graphing is an important feature of the field of applied behavior analysis, not only as a job responsibility of behavioral professionals, but as a visual analysis tool as well. While graphing can be taught using various methods, perhaps self-training methods could prove both effective and efficient due to the self-guided nature of the methods. One effective self-training method for graphing is enhanced written instruction (EWI). While the literature has demonstrated EWI’s effectiveness when training graphing, specific presentations of EWI have not been evaluated. To address this gap in the literature, we compared accuracy of and duration to graph completion of chunked presentations of EWI, and evaluated preference for the two different chunked presentations, using concurrent chains schedules embedded within a nonconcurrent multiple baseline design across five students with various degrees of graphing history. Both chunked presentations were found to be effective, with most participants clearly preferring one presentation over the other. These results will be discussed in the context of next steps for research and practice related to teaching graphing.

 

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