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This exploratory study aimed to investigate the characteristics of students who opted-in to use Boost, an automated student support mobile app and compare characteristics of non-Boost users. Boost is a mobile app that integrates with the Learning Management System (Canvas) and provides support services aimed at improving student behavior and success. At the start of the Spring 2019 semester at Indiana University, instructors were invited to opt-in for Boost to be available to their classes. Instructors who opted-in invited their students to use Boost. Our multivariate analysis of variance (MANOVA) compared those who opted-in for automated support with those who did not (n=158 courses). Findings reveal that opt-ins were more likely to be Asian, International, and despite having higher college entrance exam scores and being farther along in their studies, opt-ins were slightly lower performing than their peers who did not opt-in. A profile of Boost users will help university administration, student support services, and instructors make data-informed decisions on optimal use of Boost.
Andrews et al. (2020) studied this question.