The Penn State EdTech Network is excited to announce that the top 10 proposals have received $5,000 each in seed money for development of their ideas for the Nittany Watson Challenge. The challenge encourages teams of Penn State students, faculty, and staff to leverage IBM Watson to improve the student experience and the selected proposals did not disappoint.
“We received 39 incredibly strong proposals in the initial phase of the Nittany Watson Challenge, and what emerged were 10 proposals that exemplify the best of the creative and innovative energy across our University,” said Brad Zdenek, Innovation Strategist for the Penn State EdTech Network. “The roughly 50 team members in these projects are spread throughout our colleges and campuses, representing undergraduate students, graduate students, faculty, and staff. What they have in common is that each is focused on leveraging the capabilities of Artificial Intelligence to create a better experience for both current and prospective students at Penn State.”
The top 10 proposals are tackling five main topics including academic advising, credit transfer, student opportunity matching, assisted note taking, and office hour optimization. By using a plethora of IBM Watson capabilities, each team is determined to prove that given the opportunity, the power of artificial intelligence has the capability to vastly improve and positively impact the student experience at Penn State.
“IBM is thrilled with the broad engagement of this challenge across the entire university fabric and we’re encouraged by the level of detail and expertise we’ve seen thus far in the proposals,” said on-campus IBMer, Rich Prewitt. “It’s exciting to see Watson’s broad capabilities on display within each team’s framework of solutions.”
See below for an overview of the proposals submitted:
- Academic advising – four teams submitted proposals to tackle the time-intensive process of academic advising. An advising FAQ chat bot, automated advisor, and cloud-based course recommendation system are potential solutions to ensure that prospective and current students make better decisions on which careers they want to pursue and how that will impact their course schedule and finances at Penn State.
- Credit transfer – two team’s submitted proposals that would create a process currently not in place at Penn State for evaluating credit transfers for prospective students. While one team is proposing a pre-evaluation of transfer credits, the other team is proposing a course matching program. Both teams will attempt to use Watson to create a solution that will improve the student experience, retention rates, and create a more sustainable process across the University.
- Student opportunity matching – two team’s submitted proposals to create an opportunity matching application that would be a resource for prospective or current students to find other students or groups with similar interests. When attending a large university, such as Penn State, finding a group to belong to and get involved with can exponentially improve the student experience and also help retention rates for prospects. By using IBM Watson in this way, both groups look to teach students about what Penn State has to offer with personalized suggested opportunities.
- Assisted Notetaking & Office Hour Optimization – while two teams submitted proposals on different subjects, they both are looking to tackle inefficient processes that both faculty and students are spending exponential time on. For example, one team is proposing the use of AI assisted notetaking which will use Watson features to create one cohesive and complete transcript of each class. In addition, professors can then see what students actually understood from the lecture and analyze past data to identify what areas need greater instruction in a much more quantitative way than what is currently available. The other team is proposing an office hour’s optimizer to allow students to receive pertinent information about their specific needs and also minimize office hours along with maximizing office hour efficiency for professors.
Each of the 10 teams will use their first-round seed money for development. After a second round of judging, a panel will select five projects to receive an additional $10,000 each in funding for further development of a minimum viable product. Learn more about the Nittany Watson Challenge.