UNIVERSITY PARK, Pa. — A Penn State team is working with artificial intelligence technology to find a solution to the cumbersome task of approving transfer credits for students wishing to enroll at the university from another institution. The team is part of the Nittany Watson Challenge, a Penn State EdTech Network initiative with IBM that began in January.
After two rounds, five teams were selected as finalists and given $10,000 each to come up with a minimum viable product by the end of July.
The team tackling the transfer credit challenge is made up of admissions and financial aid directors, transfer credit specialists, web strategists and doctoral candidates from Penn State's Eberly College of Science and College of Engineering.
Daren Coudriet, director for the Penn State EdTech Network, said determining how course credits will transfer from one university to another is often complex and manually intensive, and is critical to helping students determine the cost of their degree.
“Penn State is examining how this process can be automated using artificial intelligence and machine learning to provide students with the information they need to make an informed decision,” Coudriet said. “We want to solve this problem not only for Penn State, but for other higher ed institutions struggling with this same problem.”
Laura Anderson, assistant director for admission services and financial aid for Penn State World Campus and project team lead, said by using IBM Watson, the team hopes to shorten the length of time it takes to give students the answers they need and provide additional services to ease their transition.
“Our current process requires students to apply and obtain an offer of admission prior to receiving transfer credit review. Staff from several units across the University manually complete much of this labor-intensive process, which results in less time to be proactive with students on higher-level issues related to their academic success,” Anderson said. “Our proposed solution serves a core need for the University and if we are able to create a solution — even in a portion of the transfer credit review process — it can help us to work towards a more sustainable model. Due to the complex and manual nature of Penn State’s transfer credit evaluation process, we felt that an intelligent technology solution was key and saw great potential in IBM Watson.”
Richard Prewitt, chief test engineer for IBM Systems, said teams are accessing Watson through the IBM Bluemix cloud platform.
“Bluemix supports various programming languages with Watson services as well as an integrated capability to build, run, deploy and manage applications on the cloud,” Prewitt said.
The teams participating in the Nittany Watson Challenge are utilizing Natural Language Understanding, Tone (sentiment) Analysis, Tradeoff Analytics, Speech-to-text/Text-to-speech Conversion, Conversation Agent and Document Conversion to create their minimum viable products.
Anderson said the challenge has given the team an opportunity to think critically and creatively about how to solve a serious component for student success.
“Many of our team members work with students every day, so we understand the importance of transfer credits and the challenges that the process of transferring can present,” Anderson said. “Being able to experiment with artificial intelligence on a project that could positively impact the student experience has been really empowering and motivating for us.”
The other finalist teams in the Nittany Watson Challenge are working to create a virtual adviser, a program to help connect Penn State students on campus, and a model for compiling notes taken by students in class.
To learn more, visit the Penn State EdTech Network online.