As you may have heard, we are in the second year of offering teams of Penn State students, faculty, and staff the chance to compete for grants totaling $100,000 by leveraging artificial intelligence (AI) to improve the student experience at Penn State. Last year, we hosted the Nittany Watson Challenge in partnership with IBM, and this year, we allowed competitors to leverage AI technologies from a larger group of AI companies in the Nittany AI Challenge.
Since we’re halfway through this year’s Challenge (check out the phase 2 winners!), we wanted to check in with some inaugural Challenge participants. Read below to learn more about how a Penn State staff member, faculty member, and student leveraged their participation in the Challenge to get to where they are today.
Name: Laura Anderson
Role: Assistant Director, Admission Services and Financial Aid, Penn State Outreach and Online Education
Minimal Viable Product: Utilizes matching technology (natural language processing and a proprietary model built by the team’s developer) to assess how a course lacking an official transfer decision at an institution could potentially transfer into another college or university.
After hearing about the Challenge and attending initial information sessions, Laura saw potential in leveraging artificial intelligence to create efficiency around an organizational problem, transfer credits. “At a large institution, it can be difficult to find avenues where you can make an impact,” said Laura. “I decided to participate in the Challenge because I wanted to contribute to change or at least feel like I had the freedom to explore what change might look like. I wanted to experiment with no boundaries in a way that is often out of the scope of my regular work, but would still connect back to making the higher education experience better for our students.”
The TransferMatch team was composed of subject matter experts who worked with transfer credit and transfer matching on a daily basis. Laura credits their Challenge success to their team dynamic. “From start to finish, the project was a complete collaboration among the team. Our team understood the transfer credit challenges holistically, from the perspective of the student and staff, as well as the resources available (or in some cases not available) within the University to help source a solution to this problem,” said Laura. “We live the transfer credit pains every day, so it was an opportunity to band together and try to do something important together.”
As a Penn State staff member, Laura remarked on how the experience has impacted her career. “Having the opportunity and designated time to focus on considering solutions to that particular issue, and further, experiment with how technology could support those solutions was a great example of what I enjoy about the work that we can do at a place like Penn State World Campus,” said Laura.
When asked if she would recommend the Challenge participation to other staff members, Laura remarked, “The Challenge was really a unique opportunity and I would absolutely recommend other Penn State staff members to get involved in future iterations as a way to challenge themselves and challenge the status quo. The value of the Challenge is that it provided a platform to problem solve, experiment, and advocate around an issue that affects students.”
Name: Dr. Meng Su
Role: Chair and Associate Professor, Department of Computer Science and Software Engineering, Penn State Erie, The Behrend College
Team: Professor Nittany
Minimal Viable Product: Utilizes artificial intelligence to provide answers to student questions covering a range of topics, such as admissions, course enrollments, tuition and fees, financial assistance, and other academic help.
After being exposed to a project in summer 2015 where Erie Insurance Company and Penn State Behrend collaborated with IBM Watson to create a pilot project, Dr. Meng Su realized the impact that artificial intelligence would have on the future and prepared a course to introduce that technology to students. When he found out about the Nittany Watson Challenge, it was a great fit. “As a computer science and software engineering professor, I want to help connect my students with this rapidly growing industry when it comes to machine learning and artificial intelligence,” said Dr. Su. “This was a great opportunity to equip them with necessary resources, skills, and expertise from industry professionals as they learn and advance in their careers.”
Dr. Su leveraged the Challenge to provide real-world experience to his students that complimented their classroom learning. “I think the Challenge reflects the mission of the Penn State EdTech Network, which is to foster relationships among the university, industry leaders, and entrepreneurs,” said Dr. Su. “Our experience strongly aligns with this when we consider the collaboration we have had across leading technologies in industry (vendors), users (customers), and educators. This is a wonderful model and provides unique opportunities for our students.“
As a Penn State faculty member, Dr. Su commented on how his Challenge experience impacted his career. “As a professor, I want to be able to educate and enable our students to be more successful, as our program empowers more graduates to become the future innovators and entrepreneurs.” Dr. Su went one step further and talked about how his experience is impacting his current work. “I am the department chair of Computer Science and Software Engineering at Behrend. We are working on enhancing our curriculum with a new artificial intelligence concentration and building more collaborations with industry through our senior design project program.”
Reflecting on his experience and the value of participating in the Challenge, Dr. Su said he’d definitely recommend other Penn State faculty members get involved in the future. “As the team leader and faculty member of this project, my main role was to help design the project and its architecture, give directions on methods and resources, coordinate the teamwork, and most importantly, to empower team members with vision and insight on the values.”
Name: Adam Niederer
Role: Penn State Class of 2018, BS in computer science and a minor in mathematics
Team: Collanote: Making Note-Taking Great Again
Minimal Viable Product: Utilizes artificial intelligence to provide a central hub for note-taking in each class, offering collaborative notes, full search capabilities, dynamic Q&A, and lecture transcription for students in real time on one shared document.
After learning about the Nittany Watson Challenge through participation in the fall 2016 HackPSU, Adam and his friends decided to enter the Challenge. “My team and I loved competitions, and the topic seemed to fit our interests,” said Adam. “My teammate, Joe, was familiar with the startup scene in State College, and thought this was a good opportunity to jump into another project after he sold his last venture. I wasn't super familiar with machine learning at the time, and this looked like a good excuse to pick it up.”
One of the goals of the Challenge was to provide out-of-classroom experiences for Penn State students. Adam was one such student that spoke about his participation. “The Nittany Watson Challenge was definitely the highlight of my semester last spring, and had an overwhelmingly positive impact on my educational experience,” said Adam. “It let me augment my theoretical experience with team management, software engineering experience, and some technical writing and speaking for our pitches and presentations.”
The Collanote team, comprised of all students, kept that perspective in mind when building a solution that aimed to increase efficiency of an action that every learner is tasked with as part of their learning experience, taking notes. “Being able to work with a team on something both real and cutting-edge is definitely a valuable experience.”
When asked if he would recommend an opportunity like this to his peers, Adam notes, “Students, especially, would benefit greatly from the challenge for the experience alone.”
As with most students, Adam leveraged the Challenge as an opportunity to gain experience to help him stand out from his peers when looking for internship and job opportunities. “Getting some exposure to machine learning techniques while building something that can run as a production application is a rare experience which definitely helped me stand out from the crowd,” said Adam. “Every recruiter and hiring manager I've spoken to has fawned over Collanote since I listed it, and I've gotten more responses and offers than I can handle in part because of it.”
As we look forward to the last phase of the Nittany AI Challenge, we are excited to see how this year's Challenge cohort will take forth their learnings and experiences to impact the student experience at Penn State and beyond.