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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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43rd Annual Convention; Denver, CO; 2017

Event Details

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Symposium #316
CE Offered: BACB
Training Applied Behavior Analytic Skills Using Advanced Technologies
Sunday, May 28, 2017
5:00 PM–5:50 PM
Convention Center 304
Area: TBA/EDC; Domain: Applied Research
CE Instructor: Azure Pellegrino, M.A.
Chair: Azure Pellegrino (Utah State University)
Abstract: Training applied behavior analytic skills to individuals who provide services to clients is a critical area of development. As technology advances, so do the possibilities of developing effective and efficient training. This symposium investigates some of these possibilities. Computer-based training can be self-paced and include lectures, video examples, and interactive activities. Gerencser, Higbee, Contreras, Pellegrino, and Gunn investigated this format on training paraprofessionals to implement errorless discrete trial instruction. Scott and Lerman also evaluated this format on training teachers to detect potential antecedents and consequences of problem behavior. Other technologies that can be used in training are video modeling and enhanced written instructions. Berkman, Roscoe, and Bourret compared the effects of each of these training methods on graduate students' acquisition of creating single-subject design graphs using GraphPad Prism. The potential advantages and future directions of using each of these training methods are discussed.
Instruction Level: Basic
Keyword(s): computer training, Prism, teacher training, video modeling
Evaluation of Interactive Computerized Training to Teach Paraprofessionals to Implement Errorless Discrete Trial Instruction
KRISTINA GERENCSER (Utah State University; Marcus Autism Center), Thomas S. Higbee (Utah State University), Bethany P. Contreras Young (Utah State University), Azure Pellegrino (Utah State University), Summer Gunn (Utah State University)
Abstract: Training paraprofessionals who work with children with disabilities can be challenging due to limited resources. Alternative ways to train paraprofessionals on a larger scale is needed. Interactive computerized training (ICT) – a self-paced program that incorporates audio narration, video models, interactive activities, and competency checks – is one potential solution. ICT has been successful at training college students and special education teachers to implement discrete trial instruction, but its effectiveness to train paraprofessionals is unknown. The purpose of this study was to evaluate the utility of ICT, using a multiple-baseline design, to teach six paraprofessionals to implement discrete trial instruction and an errorless learning procedure. Following the training, the fidelity of implementation of discrete trial instruction increased for all participants, at varying levels, when implemented with students in their classrooms. We evaluated the effects of providing remote feedback and coaching on fidelity. We also evaluated generalization to novel programs and maintenance.
Computer-Based Instruction for Training Teachers to Detect Potential Antecedents and Consequences of Problem Behavior
JELISA SCOTT (University of Houston-Clear Lake), Dorothea C. Lerman (University of Houston-Clear Lake)
Abstract: Training teachers and paraprofessionals to detect and record putative antecedents and consequences of problem behavior in the classroom has a number of benefits. In this study, we evaluated the outcomes of a computer-based training program consisting of lectures, models, and practice. A total of 38 teachers and paraprofessionals with limited experience in collecting descriptive assessment data participated. Participants scored videos of teacher-student interactions after completing components of the computer-based instruction. The study was designed to determine (a) if training with single exemplars of common antecedents (e.g., demand delivery) and consequences (e.g., reprimands) would produce generalization across multiple exemplars, and (b) if training with single antecedents and consequences would produce generalization across simultaneously occurring antecedents and consequences. Results indicated that single exemplar training was adequate for most participants to detect untrained exemplars. However, training that specifically targeted the detection of simultaneously occurring antecedents and consequences was necessary for the majority of participants. These data support the efficacy of computer-based training and indicate the necessary and sufficient components of this training.
Comparing Procedures for Training Staff to Create Single-Subject Design Graphs Using GraphPad Prism
SYDNEY J BERKMAN (New England Center for Children), Eileen M. Roscoe (The New England Center for Children), Jason C. Bourret (New England Center for Children)
Abstract: An important skill for behavior analysts is creating graphs that clearly convey intervention outcomes. Prior research has documented the shortcomings of Microsoft Excel (e.g., Su, 2008; Vanselow & Bourret, 2012). GraphPad Prism allows for editing that aligns with graphing conventions, but initial training is needed. Two effective self-directed training methods are video modeling (VM; e.g., Collins, Higbee, & Salzberg, 2009; Moore & Fisher, 2007) and enhanced written instructions (EWI; e.g., Graff & Karsten, 2012), but no single-subject studies have compared the efficacy of the methods. In this study, we compared the efficacy and social validity of EWI and VM for training staff to create graphs using Prism. In Study 1, a single-subject design was used to compare the effects of the methods on the individual performance of 11 graduate students. In Study 2, a group design was used to compare the effects of the methods across a greater number of graduate student participants (n = 28). EWI and VM were both found to be effective, and no significant differences in accuracy or speed were found. Mean interobserver agreement for both studies was above 95%.


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