20771
Technology-Based Intervention to Teach Mathematics Skills to Students with Autism

Saturday, May 14, 2016: 1:45 PM
Room 309 (Baltimore Convention Center)
G. Yakubova1, E. M. Hughes1 and M. Shinaberry2, (1)Duquesne University, Pittsburgh, PA, (2)Duquesne University, Pittsbrugh, PA
Background:  

Research examining video-based interventions and other instructional strategies to determine evidence-based practices for students with autism spectrum disorder has been limited to social, behavioral, communication, and daily living skills. Limited attention to teaching academic skills necessary for independent life can be disadvantageous given the necessity of at least basic academic skills to perform daily life activities, such as purchasing, managing the budget, and others. Students with autism spectrum disorder (ASD) face many challenges learning mathematics yet limited research supporting interventions exist in this area. Additionally, the economic development in the 21st century and rise of jobs that require at least some level of academic skills necessitate teaching of academic skills necessary for various aspects of post-school adult life. The presentation describes the results of the study examining the effectiveness of technology-based concrete-representational-abstract sequencing instruction in teaching mathematics skills to students with ASD.

Objectives:  

The purpose of this study was to determine the effectiveness of video modeling intervention with concrete-representational-abstract (CRA) instructional sequence in teaching mathematics concepts to students with ASD. 

Methods:  

A multiple baseline across skills design of single-case experimental methodology was used to determine the effectiveness of the intervention on the acquisition and maintenance of mathematics skills for students with ASD. Three different mathematics skills were targeted for each participant based on their individual education goals. Students participated in a minimum of five baseline sessions, 11 intervention sessions, and three maintenance sessions during a three-week follow-up period. Data were analyzed using the recommended approaches for single-case experimental data: visual analysis analyzing for trend, level, variability, magnitude of effect and effect size calculation to determine the existence and magnitude of a causal relationship between an intervention and target skills (Kratochwill et al., 2013).

Results:  

Results demonstrated that each student solved mathematics problems with improved accuracy during intervention compared to baseline levels. The intervention had a strong effect on students' skill acquisition and maintenance.  Students’ response accuracy improved from the mean of as low as 0 to 3% to as high as 61 to 100% accuracy. Two main findings were found: (1) increase in students' responses on addition, subtraction, and number comparison problems from baseline to intervention phases, suggesting the effectiveness of a technology-based intervention and (2) continued response accuracy at a three-week follow-up assessment for all skills for three of four students.  Students and teachers also held positive perceptions on the effectiveness and practicality of the intervention.

Conclusions:  

The findings of the study contribute to interventions on teaching mathematics skills necessary for further success in school and post-school life via technology-based instruction in a student-centered manner. This can provide valuable contributions for research and practice in the education of students with ASD. Findings offer potential for future research in examining this under-researched area of using CRA with technology in teaching students with ASD. It also offers implications for practice in using technology combined with other strategies to improve skill acquisition and learning outcomes of students with ASD.