Profiles of Classroom Active Engagement Among Early Elementary Students with Autism Spectrum Disorder

Friday, May 13, 2016: 5:30 PM-7:00 PM
Hall A (Baltimore Convention Center)
N. J. Sparapani1, V. P. Reinhardt2,3, L. Morgan2, C. Schatschneider2 and A. M. Wetherby2, (1)Arizona State University, Tempe, AZ, (2)Florida State University Autism Institute, Tallahassee, FL, (3)JFK Partners Universiy of Colorado School of Medicine, Aurora, CO
Background: Classroom active engagement is essential for effective educational programming for students with Autism Spectrum Disorder (ASD; National Research Council, 2001). However, students with ASD display constellations of challenges that may interfere with active engagement in classroom activities. A recent study using the Classroom Measure of Active Engagement (CMAE), a multidimensional observational tool, reported a pattern of overall limited yet variable active engagement in elementary students with ASD in classroom activities (Sparapani, Morgan, Reinhardt, Schatschneider, & Wetherby, 2015). Identifying profiles of active engagement may guide effective programming for students with ASD by describing patterns of skills and behaviors that influence classroom performance and learning.

Objectives:  The purpose of this study was to identify profiles of active engagement within a sample of elementary students with ASD using the CMAE.

Methods: Participants included 196 students with ASD and their educators (n = 126) in kindergarten through second grade (M = 6.36 years, SD = 1.01) who were video-recorded in their classrooms at the beginning of the school year. This study used latent profile analysis (LPA), a statistical method for identifying subgroups of individuals that share characteristics (Jung & Wickrama, 2008) to define distinct profiles of active engagement in elementary students with ASD. LPA was used to compare models with two, three, four, and five profiles based on seven components of active engagement from the CMAE including productivity, eye gaze, responding, directed communication, generative language, flexible behavior, and flexible attention.

Results:   Preliminary findings indicated that four latent profiles best described classroom active engagement within the sample (Entropy =.94), showing excellent overall model fit, the best fit in comparison to competing models, and strong overall membership probability (0.93 to 0.98). Below is a brief description of each profile.

Profile 1, the largest profile (64%), was characterized by limited eye gaze (1.5 SD below the mean) and less frequent directed communication and generative language (0.5 SD below) than each of the other profiles. Students in Profile 2 (12%) exhibited greater classroom active engagement than each of the other profiles, showing the highest frequency of eye gaze (5.5 SD above), directed communication (2 SD above), and generative language (1.5 SD above). Profile 3 (18%) was also characterized by a higher frequency of eye gaze (5 SD above); however each of the other active engagement components appeared to be within the typical range compared to the total sample. Profile 4, the smallest profile (6%), was characterized by a higher frequency of generative language (1.5 SD above) than directed communication and responding (approaching 1 SD above), and students’ frequency of eye gaze was below the sample mean (approaching 0.5 SD).

Conclusions:   These findings indicate that components of active engagement form constellations of skills and behaviors that vary among elementary students with ASD. This study provides preliminary data about a promising method to identify profiles of active engagement, which may help guide educational programming and support educational outcomes in elementary students with ASD.