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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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44th Annual Convention; San Diego, CA; 2018

Event Details

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Symposium #88
Diverging Perspectives on Digital Technology
Saturday, May 26, 2018
3:00 PM–3:50 PM
Manchester Grand Hyatt, Grand Hall D
Chair: Christopher E. Bullock (Kennedy Krieger Institute)
Abstract: Three different projects using digital technology to improve treatment of individuals with Autism Spectrum Disorder (ASD) are described and demonstrated. In each project, a treatment or intervention aim was addressed with an application of off-the-shelf, inexpensive digital technology. One project shows how to use iPad for acquisition of manding with an autoclitic, a second compares andrpis and IOS based high and low tech approaches to teaching basic verbal operants, and the third describes an android-based intelligent agent to direct discrete trial training. The three presentations will both describe the treatment aim, the rationale behind developing the digital technology, and demonstrate how the technology works. This latter point is crucial because it seems that too many descriptions of exciting digital technology applications leave people wondering how the technology works, looks and feels. Hence the focus of this symposium is to work through development and implementation issues, with data reporting of secondary concern.
Instruction Level: Advanced
The Acquisition of an Autoclitic Carrier Phrase Using the iPad as a Speech-Generating Device
(Applied Research)
JESSICA MILLER (University of Arkansas), Elizabeth R. Lorah (University of Arkansas)
Abstract: The use of the iPad with the application Proloqu2Gocontinues to provide practitioners with access to high capability speech-generating devices (SGD). There is a growing body of research demonstrating that the iPad and application Proloqu2Go can be used effectively as an Augmentative and Alternative Communication system for young children with autism, in terms of the acquisition of a mand repertoire. There is relatively less research looking beyond the basic mand repertoire to other operants, such as the tact or intraverbal. Comparatively, we have seen even less research on the acquisition of the autoclitic. This study evaluated the use of an iPad based SGD and a five-second time delay with full physical prompts, for the acquisition of manding with an autoclitic (i.e., carrier phrase), in three preschool-aged children with autism. Using a multiple-baseline design across participants, children were exposed to training during a snack-time routine, within a university-based clinical preschool setting. Preliminary results indicate positive trends in the use of the autoclitic "I want." Results indicate that the use of such a device for full-sentence manding is achievable. Further, these results provide additional support for the use of handheld computing devices as SGD.
Open-Source Augmentative and Alternative Communication Technology for Autism Spectrum Disorders
(Applied Research)
SHAWN PATRICK GILROY (National University of Ireland), J McCleery (National University of Ireland - Galway), Geraldine Leader (National University of Ireland)
Abstract: Effective methods for teaching social and communicative skills to individuals with autism spectrum disorders (ASD) have traditionally used low-tech approaches. Recent advances in technology (i.e., mobile technology) have resulted in high-tech alternatives to low-tech approaches (i.e., laminated picture cards), though these newer alternatives have only started to be evaluated more recently. Despite rapid adoptions of high-tech device in social and communicative teaching, there are few guidelines for how to use high-tech devices in this manner. An open-source mobile application was developed for both Apple and Android products to facilitate comparisons high-tech and low-tech forms of AAC. This study aimed to answer the following questions: 1) does the complexity of high-tech methods impact the learning of requesting skills; 2) does the complexity of high-tech methods negatively impact the learning of queried requesting skills; and, 3) does the complexity of high-tech methods negatively impact the learning of queried social responding. School-age children were randomly assigned to one of two types of AAC intervention and interventions were provided in the child's school. Trained clinicians provided participants with either a high-tech (n = 18) or low-tech (n = 17) form of communication training. Participants were assessed prior to, and following, approximately four months of intervention. The results of this trial found that children with social and communicative impairments improved in these areas following intervention with high-tech and low-tech forms of AAC. Additionally, the outcomes from these two approaches did not differ significantly in overall outcomes. Despite encouraging results, additional research is warranted to explore the relative efficacy of high-tech approaches with children who may have multiple, and more substantial, levels of impairment. The software will be demonstrated with a range of commonly-used touchscreen devices. The aim of the project was to develop a platform that could be easily adapted for use with "off the shelf" products at a range of price points. The functioning program, and its use, will be demonstrated with both high-end Apple and medium- to low-end Android products (50-100 Euro cost devices).
Usability Evaluation of an Intelligent Agent to Guide Discrete Trial Therapy and Perform Data Analytics
(Applied Research)
DONALD A. HANTULA (Temple University), John Nosek (Temple University), Matthew Tincani (Temple University), Judith Stull (Temple University), Slobodan Vucetic (Temple University), Tian Bai (Temple University), Ashis Chanda (Temple University), Shanshan Zhang (Temple University)
Abstract: With turnover rates over 40%, autism service providers struggle to maintain program fidelity across instructors with varying experience, while reducing non-instructional time writing reports, coping with lacking data integrity and overcoming problems inherent in paper-based systems. Transformational technology in the form of an android-based intelligent agent provides unique, real-time process and decision support for instructors while automatically collecting quality, granular data that can be mined. The technology supports instructors in the decisions they need to make before and during instruction. Using student performance, mastery criteria, instructor identity, location and date, the technology identifies what the instructor should do next. It automatically collects data in a way that instructors can focus on the child. For instructors and family members who need it, it provides detailed, step-by-step guidance, updated in real-time based on student performance that coaches them in what to do, how to correct and when to reinforce. In addition to assisting supervisors in program evaluation and customization through descriptive and predictive analytics, prescriptive analytics alter and optimize instruction in real-time based on student past and current performance. Pilot tests of increasing complexity and length conducted over two years at a large regional autism service provider showed that student performance improved.



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