Capturing attrition decisions in engineering graduate students using longitudinal SMS data

This research paper reports results from a longitudinal Short Message Service (SMS) text message survey study that captured attrition decisions from engineering graduate students who decided to leave their Ph.D. program or change degree objectives from Ph.D. to M.S. (Master's-level departure). While past research has investigated doctoral attrition across disciplines to identify various factors that influence students' ideas of leaving (e.g., advisor, funding, lack of well-being), departure is often the result of a series of negative experiences that impact students over time, making it difficult to capture in retrospective interview-based studies. To overcome this issue, we captured the experiences of N = 142 current engineering Ph.D. students across the US over the course of a year, collecting data three times per week using SMS text message survey methods. After the first year of the study, we captured doctoral departure in a subset of our participants who decided to leave their Ph.D. programs while enrolled in our study. This study is the first to capture and show attrition decisions in action. It combines real-time understandings of stress and participants' decisions to depart. The results are transformative in gaining insight for the monitoring and understanding attrition in higher education.