Formulating Predictive Models of Engineering Student Throughput

Engineering degree acquisition is a complex system that lacks tools for efficient management and goal optimization. A reliable model of engineering degree acquisition will help administrators to increase throughput and resource utilization. It will also aid engineering students in better managing their educational investment. A method is needed to quantitatively assess the factors that predict time to graduation for engineering students; explore the potential positive effects of intervention to affect critical factors; and examine the costs vs. benefits of increasing engineering student throughput rates. Changes in student course-taking patterns and degree requirements have lengthened the time to graduation for typical engineering students. This reduces the number of students educated in a four year time period and consumes additional resources in course enrollments, faculty time, and support staff labor. With tuition costs rising faster than inflation, the trends have undesirable results for both universities and students. This paper reviews the relevant literature in order to begin developing a study design to model student progression through engineering degree acquisition as a complex system. Elements are expected to include transition probabilities, identifying critical factors, predicting time to graduation, estimating costs and benefits of potential interventions, and projected throughput of engineers earning bachelors’ degrees. The main goal of the research is to achieve an actionable, applicable, and accurate decision modeling method for a student’s progress to an engineering degree and a university’s resulting throughput rate to provide decision-making tools for both students and administrators. The longer term goal is increasing STEM persistence and throughput.