Emu: Engagement Modeling for User Studies

Proc ACM Int Conf Ubiquitous Comput. 2017 Sep:2017:959-964. doi: 10.1145/3123024.3124568.

Abstract

Mobile technologies that drive just-in-time ecological momentary assessments and interventions provide an unprecedented view into user behaviors and opportunities to manage chronic conditions. The success of these methods rely on engaging the user at the appropriate moment, so as to maximize questionnaire and task completion rates. However, mobile operating systems provide little support to precisely specify the contextual conditions in which to notify and engage the user, and study designers often lack the expertise to build context-aware software themselves. To address this problem, we have developed Emu, a framework that eases the development of context-aware study applications by providing a concise and powerful interface for specifying temporal- and contextual-constraints for task notifications. In this paper we present the design of the Emu API and demonstrate its use in capturing a range of scenarios common to smartphone-based study applications.

Keywords: Context-aware; Frameworks; H.5.m [Information interfaces and presentation (e.g., HCI)]; Miscellaneous; D.3.3 [Language Constructs and Features]; engagement; just-in-time assessment; mhealth; mobile applications; push notifications; user studies.