Admission tools and academic performance: evidence from a first course in a bachelor’s degree in business administration

Abstract

[EN] Admission tools have become imperative means for private schools to handle both limited space and the search of excellence. We use a supervised algorithm to predict the score of admitted students in a private-run Spanish business school. The main target is understanding the effects of the features defined in the admission process to assess both the validity of the process and the final ranking of the student after one year in the school, trying to ascertain what is the best mix of the variables in place to forecast the final score of the students when ending their first year in the BBA; along with the mix, we also want to define the decision rules allowing the best prediction. The results will prove that the present admission process in place is working properly even if some fine tuning could be set in place for an even better performance.