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Nittany AI Challenge Top 10 Proposals Tackle University Issues

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Nittany AI Challenge Top 10 Proposals Tackle University Issues

March 7, 2018

The Penn State EdTech Network is proud to announce that phase one of the Nittany AI Challenge yielded 71 proposals from 254 unique participants representing 10 campuses and 16 colleges at Penn State. A committee comprised of University officials and industry participants whittled down the proposals to the top 10 teams which all received $2,500 in seed money for development of a prototype.

“This year, we received an amazing number of proposals, representing a host of innovative ideas from across the University community,” said Brad Zdenek, Innovation Strategist for the Penn State EdTech Network. “With the help of University administrators and content experts in the field of AI, we selected 10 proposals to support in prototype development. We feel those proposals truly represent groundbreaking ideas, leveraging the latest in artificial intelligence and machine learning, to improve the student experience at Penn State and beyond.”

The top 10 proposals are utilizing a myriad of artificial intelligence platforms to develop solutions that improve the student experience at Penn State and solve operational issues that the University is facing. The team members' unique experiences coupled with AI technology sets forth proposals that are aimed at improving efficiency and increasing collaboration across Penn State.

"As we evolved from the Nittany Watson Challenge last year to the Nittany AI Challenge this year, we are proud to provide participating teams of Penn State students, faculty, and staff direct access to leading AI and edtech companies," said Daren Coudriet, Director of the Penn State EdTech Network. "From critical training resources to one-on-one consultation, each company provides a unique perspective and capability to help the participating teams create solutions that will positively impact higher education."

See below for an overview of each of the top 10 proposals chosen to move through to the next round of the challenge:

  • Aspire – application that helps students map out their college career by providing recommendations on experiences and skills needed to achieve their dream job post-graduation.
  • Course Recommendation System Using Historical Student Course Enrollment and Performance – course recommendation system that learns from students’ past courses and performance to recommend courses (outside a student’s major requirement) that most closely matches their interests.
  • FeelLike – cross-platform mobile app that extends the student experience outside of the classroom where users post what they want to do, the intended activity is anonymously sent out to other users to gauge interest, and whenever accepted by a mass of individuals, is planned accordingly thus strengthening connections through engagement opportunities.
  • From Micro to Macro: Applying Machine Learning to Scale up Competency Based Learning at PSU – solution that evaluates information literacy digital badges; specifically analyzes course materials and evaluation of student responses so that Penn State can offer digital badges at quality, speed, and scale for additional courses.
  • Intelligent Prediction System Using Emotion Classification – emotion prediction system that automatically collects data from social media; analyzes the emotions and sentiments associated with topics and makes predictions on events.
  • Lion Planner – application that will make opportunities, such as clubs and courses, offered to students at Penn State more accessible by providing guidance that will reduce the complexity of scheduling and introduce users to new activities and electives that align with their interests.
  • Pathfinder: Recommending Course Pathways – app that recommends effective course pathways meaning it will allow students to seamlessly browse, plan, and select courses that will improve the way in which students plan their curriculum.
  • ProFound, A Professor Search Engine – solution that retrieves all of the information publicly available about a professor and intelligently categorizes and populates it into a portal that students can access to search for a professor by name and/or research area.
  • ResOpp – web-based application that serves as a single platform to match students with research opportunities and faculty with potential candidates thus accelerating collaborative faculty-student research.
  • The Nittany AI Challenge Mock Interviews – tool that conducts mock interviews and leverages AI to analyze video and speech while additionally providing feedback to the user to improve facial gestures and conversation.

The prototypes will be presented during Penn State Startup Week at the end of March. After a second round of judging, the panel will select five prototypes to receive $5,000 for further development of a minimum viable product. Learn more about the Nittany AI Challenge.

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