Exploring Classroom Behavioral Imaging: Moving Closer to Effective and Data-Based Early Childhood Inclusion Planning

Abstract

Combining digital sensor technologies offers vastly improved measurement of where adult and child speech occurs within the inclusive preschool classroom. Consensus in the literature indicates that the talk children hear is a driver of important school readiness outcomes, particularly for children with delays/disabilities. Advantages of sensors versus human observers in measuring speech include real-time recording of the frequency of adult and child talk, adult-child turns (reciprocal interactions) and peer talk over an entire day at preschool. We piloted the combining of two wearable sensor technologies in order to image classroom talk: the Language ENvironmental Analysis (LENA) and Ubisense Inc. The LENA is an automated recording and processing measure of adult, child and peer talk. Ubisense is a real-time indoor location system. The marrying of these novel technologies greatly enhances existing ecobehavioral assessment and in all likelihood our understanding of the degree that young children with disabilities can most effectively be included in mainstream classrooms. Findings include the distribution of time and speech captured in activity areas of the classroom in reference to a preschooler with a developmental delay and an illustration of adult talk displayed in heat map. These devices potential to inform future inclusion research are discussed.