The goal of this project is to implement regression models for predicting the likelihood of a freshman student in the Ira A. Fulton Schools of Engineering to return in the following spring semester. This research is built off the analysis done by Arafat and Pedroza in the spring of 2018. The models that are being
Because of the unending need for engineers, ASU has a vested interest in maintaining and increasing the retention of their first-time freshman engineering students. This research aims to utilize linear and non-linear modeling to predict student retention probabilities and identify which tools are most successful at increasing retention. The models will provide accurate predictions of
Refining models to identify at-risk freshmen will help academic advisors intervene and improve retention.
Developing targeted intervention efforts can help ASU increase retention of its engineering students.
The objective of this research is to improve the freshman retention of students in the Ira A. Fulton Schools of Engineering. The researchers identified characteristics of students who leave Arizona State University after their first year and examined significant factors by building statistical models to predict the causes of student attrition. The intent of these
Society will always need engineers, hence at ASU there is an interest on retaining as many students as possible. This research project attempts to use statistics to find factors that contribute to student retention and develop a retention plan. Using linear regression on student data, factors such as GPA, probation status, and the number of