An Analytic Model to Assist Academic Advisors

Abstract

We detail how academic advisors at two land grand universities benefit from the identification of factors related to poor academic performance of first-year students. We used a multivariate statistical model and data from one institution to identify characteristics of students at-risk of earning low grade point averages. We showed through a second application of the statistical model that first-year dropout was directly related to grade point average.