|A Glimpse into the Future: The Emerging Science of Language and Cognitive Training in Children With Autism|
|Monday, May 31, 2021|
|11:00 AM–12:50 PM |
|Area: AUT/VRB; Domain: Applied Research|
|Chair: Meagan Grasley (Utah Valley University)|
|Discussant: Jordan Belisle (Missouri State University)|
|CE Instructor: Jordan Belisle, Ph.D.|
Technological development in applied behavior analysis is emerging at a rapid pace, evidenced by the proliferation of new assessment and intervention technologies and the integration of computerized technology in data collection and programming. This symposium will put on display several new technological developments related to the PEAK Relational Training System as a standardized assessment and training strategy with children with disabilities. The first two talks will demonstrate two new technologies that can be integrated within existing PEAK programming. The first will explore eye-gaze tracking as a predictor of program mastery and success that may be more sensitive than traditional performance measures with children. The second will explore automated and gamified programming as compared to traditional delivery formats to produce rapid rates of program mastery and to improve acceptability of behavior interventions. The third and fourth talk will evaluate broader assessment and intervention outcomes with children with autism. The third will show data that replicate several prior studies on PEAK with younger children with autism to determine if previous findings hold with children below the age of 10-years. The fourth study will show new normative sample and comparative data from within the PEAK Comprehensive Assessment that can be used to inform assessment and outcome evaluations in research and in practice. Taken together, these talks show how new technologies can be integrated within PEAK.
|Instruction Level: Basic|
|Keyword(s): Assessment, Automation, Normative Data, PEAK|
|Target Audience: |
|Learning Objectives: (1) Describe how eye gaze response data can predict mastery; (2) Discuss how PEAK programs can be automated and computerized; (3) Describe normative data and age comparisons of the PCA with children with autism|
The Relationship Between Ocular Observing Responses and Relational Training Procedures for Children With Autism Spectrum Disorder
|BECKY BARRON (Emergent Learning Academy), Mark R. Dixon (University of Illinois at Chicago)|
Current research has shown differences in eye gaze, or ocular observing responses amongst individuals with autism spectrum disorder compared with their typically developing counterparts. Eye gaze is currently studied as a predictor for ASD diagnoses or potential level of social deficits for individuals already diagnosed. Deficits in language and communication are also studied as risk factors and are often attributed to social deficits in ASD. Previous research has shown improvements in accurate eye gaze during the development of stimulus equivalence classes for typically developing adults (Hansen & Arntzen, 2018). Relational training procedures that promote derived stimulus relations have also been shown to improve language repertoires for children with ASD. By combining the technology available for understanding complex language processes and eye gaze behaviors, behavior analysts may be able to better understand how to target specific behaviors in treatment that may indirectly improve eye gaze, and in turn also improve behaviors related to social interaction and attention. The current study investigated the relationship between accurate eye gaze towards stimuli during task demands and relational repertoires with children with ASD, as well as the impact that relational training has on accurate eye gaze while being taught and deriving novel, arbitrary relational frames of coordination. Results from the current study suggest a strong relationship between appropriate eye gaze and derived relational abilities, as well as increase accuracy in eye gaze as relational responding improves. These results may have implication for treatment choices for behavior analysts.
Synthesizing Technologies: Comparing Automated and Gamified Discrete Trial Training to Traditional Delivery in Children With Disabilities
|LINDSEY NICOLE HOLTSMAN (Emergent Learning STL Center ), Meredith Matthews (Missouri State University), Taylor Marie Lauer (Missouri State University), Jordan Belisle (Missouri State University), Raymond burke (Apex Regional Program)|
Discrete trial training has been supported across multiple studies as an efficient way to teach new skills consistent with a verbal behavior, stimulus equivalence, and relational frame theory approach to language and cognitive training. On the other hand, social validity and efficiency of instruction may be hindered by traditional discrete trial training systems that can become repetitive and may contain few automated reinforcers embedded within instruction. In the present study, we evaluated the efficacy of automated PEAK programs and gamified PEAK programs in promoting the development of new language and cognitive skills in children with disabilities. In a second study, we compared both delivery formats on a tablet to traditional discrete trial training utilizing physical stimuli (e.g., paper stimuli) within a multielement experimental design across participants. The first study supported the use of automated and gamified PEAK programming in teaching the target skills and achieving the transformations of stimulus function described within the programs. The second study showed that participants achieved program mastery more rapidly when programs were automated and gamified compared to traditional discrete trial training program delivery. Social validity scores were also higher when programs were delivered on a tablet. These results show a synthesis of new technologies embedded within an existing behavior analytic technology (i.e., PEAK) that can be used to teach multiple skills to develop broad performance repertoires.
The Relationship Between PEAK, Intelligence, and Challenging Behavior: A Replication With Young Children With Autism
|TAYLOR MARIE LAUER (Missouri State University
), Jordan Belisle (Missouri State University), Megan Kimzey (Missouri State University), Lindsey Schneider (Missouri State University), Hannah Wallace (Missouri State University), Kaitlin Beason (Missouri State University
Research on the PEAK Relational Training System has exceeded that of other widely available assessments and curricular packages that target language and cognition in children with autism. A salient aspect of this research are evaluations of the relationship between PEAK assessments and intelligence test scores, PEAK assessments and the function of challenging behavior, and intervention research to improve derived relational responding and intelligence test scores. The age ranges within this research have been considerable. In this series of studies, we replicate these studies with young children with autism. First, we did obtain a correlation between PEAK comprehensive assessment scores and intelligence test scores, however a weaker correlation may have resulted from overall lower performance across measures. Second, we observed that very few participants demonstrated mastery over mutual entailment items. Those who did were less likely to show a single behavior function – consistent with prior research. Thus, in both studies these relationships may still hold, but fewer children may be capable of derived relational responding as evaluated using PEAK. Finally, we conducted PEAK training over the course of 10-weeks across two children with autism who showed low levels of mutual entailment at the start of the study. Both participants demonstrated mastery of skills and increases in intelligence test scores that were approximately equal to average performance reported in prior research.
|Psychometric Prosperities and the Normative Sample of the PEAK Comprehensive Assessment (PCA)|
|MARK R. DIXON (University of Illinois at Chicago), Zhihui Yi (Univeristy of Illinois at Chicago), Ayla Schmick (Southern Illinois University)|
|Abstract: The field of behavior analysis has slowly entered the arena of standardized assessment in recent years. Besides offering benefits such as better procedural integrity, being less time consuming, and providing an age-referenced criterion, the need for such tools was further amplified as more and more behavior analytic services were covered by insurance companies, who had been interacting with mainstream psychology for decades and were familiar with using criterion-referenced tools to evaluate the repertoire of the client in question. The current study presents three overall findings on the PEAK Comprehensive Assessment (PCA). We first demonstrated significant strong correlations between the PCA and its predecessor, the PEAK Pre-assessments (PEAK-PA), while highlighting some of the benefits of adopting the PCA instead of using the PEAK-PA. We then showed convergent validity between the PCA and established measures on adaptive behavior, intelligence, and autism symptom severity. Lastly, we provided findings on the PCA’s psychometric properties, including reliability, internal consistency, and its normative sample.|