ADMIT - a web-based system to facilitate graduate admission process

Babichenko, Dmitriy; Druzdzel, Marek

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https://hdl.handle.net/2142/89301 Copy

Description

Title

ADMIT - a web-based system to facilitate graduate admission process

Author(s)

Babichenko, Dmitriy; Druzdzel, Marek

Issue Date

2016-03-15

Keyword(s)

• graduate admissions
• Bayesian networks
• machine learning

Abstract

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.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89301

DOI

https://doi.org/10.9776/16240

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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