ADMIT - A Web-Based System to Facilitate Graduate Admission

In this paper we describe ADMIT, a software application developed to assist the graduate admissions process at the University of Pittsburgh School of Information Sciences (SIS). ADMIT uses a Bayesian network model built from historical admissions data and academic performance records to predict how likely each applicant is to succeed. The system rank-orders applicants based on the probability of their success in the Master of Science in Information Science (MSIS) program and presents results as an ordered list and as a histogram to the admission committee members. The system also enables users to see a graphical representation of the model (a causal graph) and observe how each input data point affects the system’s suggestions