Automated Time Manager: Effectiveness of Self-Regulation on Time Management through a Smartphone Application

Abstract

We investigated the effectiveness of a self-regulation strategy on time management leveraged by smartphone capabilities using a theoretical framework of self-regulation that consists of four elements: 1) goal setting; 2) task strategy utilization; 3) self-monitoring and reflection; and 4) self-efficacy and intrinsic motivation. We determined the goals and strategies adopted during college life by surveying 295 college students and identified time management as a fundamental element for achieving such goals and strategies. To improve students' time management, we developed a smartphone application, automated time manager (ATM), designed to provide users with visualizations of their physical activities and phone usage reports and also to acquire smartphone sensor and usage data. From a field study of 46 college students, we highlighted three primary user experiences-awareness of unawareness, preferred feedback, and contextual but obvious use-and an overall positive time management outcome with ATM. We present an empirical study that transforms self-regulation, a well-known approach in social sciences, into computing and discusses the salient design implications for supporting time management in a more effective manner with a smartphone application.