Development of mobile applications to study engineering students’ patterns of learning

Abstract

This Research Work in Progress Paper presents a novel mobile software application created to perform ecological momentary assessment in two longitudinal studies with undergraduate engineering students. The studies collect learning activity data from first and second-year mechanical engineering students to examine the correlation of active learning with grit growth and student success and retention, and the possible associations between these factors. The software system consists of native Android and iOS mobile applications and a REST-based server application for prompting and collecting learning activity data from student participants. The system utilizes personalized student schedule data to push notifications to students on their smartphones as they complete each class or lab section. Students then submit the amount of time they spent in each class doing different types of activities including interactive, constructive, active, and passive. Students also receive notification reminders to enter out-of-class study activities. The system also includes automated daily audits and notifications to ensure consistent data entry activity. This paper will discuss the research context, early study results, software architecture, and the software development experience including institutional challenges, rationale for technology choices, strategies for developing research software with student developers, and lessons learned.