Johnson, K.T. and Picard, R.W. Proceedings of Interaction Design and Children (IDC'17), ACM Press, Stanford, CA, June 2017.

Abstract

 Current research to understand and enhance the development of children with neurological differences, including Autism Spectrum Disorder (ASD), is often severely limited by small sample sizes of human-gathered data in artificially structured learning environments.  SPRING: Smart Platform for Research, Intervention, and Neurodevelopmental Growth is a new hardware and software system designed to 1) automate quantitative data acquisition, 2) optimize learning progressions through customized, motivating stimuli, and 3) encourage social, cognitive, and motor development in a personalized, child-led play environment. SPRING can also be paired with sensors to probe the physiological underpinnings of motivation, engagement, and cognition. 

Here, we present the design principles and methodology for SPRING, as well as two heterogeneous case studies. The first case highlights enhanced attention and accelerated skill development using SPRING, while the second pairs SPRING data with electrodermal activity measurements to identify a possible physiological signature of engagement and challenge in learning.