InterViewR: A Mixed-Reality Based Interview Training Simulation Platform for Individuals with Autism
Shameem Ahmed, Wesley Deneke, Victor Mai, Alexander Veneruso, Matthew Stepita, Anais Dawson, Bradley Hoefel, Garrett Claeys, Hui Kwan Nicholas Lam, Moushumi Sharmin
Abstract
Job interviews are uniquely challenging for individuals with Autism Spectrum Disorder. While digital interview training tools have shown promising results for improving vocational outcomes for individuals with Autism, existing solutions are largely limited in the degree to which they can simulate a realistic interview environment, collect performance data from the user, and provide actionable feedback for continued improvement. To address these shortcomings and understand how to create an effective training tool, we designed InterViewR, a simulation-based interview training system that combines virtual reality and wearable smart technology in an integrated platform. Our design emphasizes an immersive user experience for training effectiveness and utilizes physiological sensing to provide intelligent affective biofeedback. We report findings from a usability study (N=11) where participants evaluated InterViewR on feasibility, usability, and perceived usefulness.