HomeBlogPodcasts AI as Friend or Foe in Computer Scienceby Matt Wittstein March 17, 2025 Share: Section NavigationSkip section navigationIn this sectionPodcasts – Home 60-Second SoTL Limed: Teaching with a Twist Making College “Worth It” Special Series First-Year Seminars Land Acknowledgement Part 1, Student Perspectives | Limed: Teaching with a Twist – Season 3, Episode 7 The use of artificial intelligence tools like ChatGPT has become the topic of serious discussion in higher education. Ryan Mattfeld, associate professor of computer science at Elon University, shares with us some of his challenges in the introductory computer science classroom and the potential negative effects AI has in training future computer scientists. He also asks what could be possible in a course where students have very few restrictions on AI use. In this first part of a two episode series, we explore student perspectives with Anna David, a first-year computer science and robotics student at Carnegie Mellon University, and graduating computer science major, Arav Patel, from the University of Maryland. Anna and Arav share insights about AI use, as well as ideas of what is really most important to students in early computer science courses. The conversation sets the stage to learn about the faculty perspective in our next episode. View a transcript of this episode. About Our Guest Ryan Mattfeld is an associate professor of computer science at Elon University in Elon, North Carolina. While mentoring undergraduate research projects at Elon, he serves as a faculty member teaching a range of computer science courses, including introductory courses, computer organization and architecture, internet of things, and cybersecurity. His research focuses on leveraging sensors for novel applications such as applying LiDAR for autonomous fire detection, respiratory monitoring, and assistive navigation for people with visual impairments. Additionally, he investigates educational methods to enhance student learning, encourage a sense of belonging in computer science, and improve assessment strategies. He has published several peer-reviewed publications on these topics. Meet Our Panel Arav Patel is a computer science student at the University of Maryland and a member of the QUEST Honors Program, where he collaborates on technology and business challenges. He has industry experience as a Software Engineer Intern at Fidelity Investments and startup experience as an AI Engineer at Mindgrasp AI, working on AI-driven solutions in finance and education. Passionate about artificial intelligence, Arav has developed AI-powered voice agents, retrieval-augmented generation (RAG) systems, and tools that enhance user interaction with complex documentation. He is also the founder of PlayGold AI, a startup focused on transforming API documentation into dynamic, AI-driven experiences. Beyond his technical pursuits, Arav enjoys exploring how AI can shape the future of learning, making technology more accessible and intuitive. Anna David is a first-year student at Carnegie Mellon University School of Computer Science, majoring in computer science and robotics. She is part of the ScottyLabs app development club and is working with a PhD candidate on robotics research. She was an AI Intern at Cogo Labs in summer 2024 and a Software Intern at UNH Interoperability Lab in summer 2023. Episode Credits This episode was hosted by Matt Wittstein and produced by Matt Wittstein and the Elon University Center for Engaged Learning, with editing and production support by Olivia Taylor. Episode art created by Matt Wittstein and Olivia Taylor. Original music by Kai Mitchell Resources Related to this Episode Center for Engaged Learning Resources The Affordances and Risks of Generative AI for Training Undergraduate Researchers Undergraduate research is credited with helping students develop cognitive abilities along with an understanding of the way that research happens, among other benefits, when done well. Some characteristics of high-quality undergraduate research include working on unsolved research problems (Bhattacharyya, Chan, and Waraczynski 2018) working closely with faculty having some autonomy in the research decisions (Gilmore et… Future of Feedback in the Age of GenAI 60-Second SoTL – Episode 86 What is the future of feedback in higher education in the age of GenAI? This episode features an open-access article that posits four key values for integrating GenAI feedback into care-full feedback encounters: Winstone, Naomi… Assessment in the Upside Down: Academic AI with Students as the Audience Recently, I downloaded Grammarly’s 2025–26 AI Trends Report. It had an interesting statement in its introduction: “Higher education is no longer at the beginning of its AI journey, but clarity of direction is still emerging” (2). Given other things I… Academic AI and Audience: Thoughts for Research Would you use AI to create materials for a tenure portfolio? How about a reference letter for a student’s graduate school application? For a conference? If so, what would you do with it? As faculty consider the risks and benefits of AI use, one area to think about is the… 1 2 … 12 13 > Other Resources “Artificial Intelligence and Your Teaching.” Elon University. Accessed March 10, 2025. https://www.elon.edu/u/academics/catl/tlresources/artificial-intelligence-and-your-teaching/. “A Generative AI Primer.” EDUCAUSE Review. Accessed March 10, 2025. https://er.educause.edu/articles/2023/8/a-generative-ai-primer. “Teaching Writing with Generative AI.” Elon University. Accessed March 10, 2025. https://www.elon.edu/u/academics/writing-excellence/teaching-writing-with-generative-ai/
