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Pace University Professor's Research Projects Showcase Student-Faculty Collaborations and AI Innovations

Strategic Insights

— 1 min read

Mary Tedeschi, a professor at Pace University's Seidenberg School of Computer Science and Information Systems, has been guiding students through research projects that have led to presentations at two prestigious international virtual education conferences: INTED 2025 and EDULEARN 2025. Working alongside undergraduate and graduate students, and in collaboration with peers from NYU and City Tech CUNY, Professor Tedeschi's research has bridged technical innovation, pedagogical advancement, and human-centered design.

Key Takeaways:

  • Professor Tedeschi's research projects, which explore the use of artificial intelligence in student advising and foundational programming patterns, demonstrate the real-world impact of student-faculty research partnerships central to the Pace experience.
  • At INTED 2025, Professor Tedeschi and her team presented two projects: "Teaching the Iterator Pattern in Introductory Programming Courses" and "AI-Powered Customer Support for Academic Counseling and Career Guidance".
  • The first project used a combination of visual tools, hands-on-practice, pair programming, and alternative teaching approaches to improve student comprehension of introductory programming courses, resulting in improved student comprehension and appreciation for the hands-on approach.
  • The AI-Powered Customer Support project assessed how AI tools can provide scalable, personalized, and around-the-clock guidance to students, but also outlined key ethical challenges, including mitigating algorithmic bias and ensuring data privacy.
  • At EDULEARN 2025, Professor Tedeschi and her students unveiled a technical, future-facing project: the development of an AI-driven database system designed to make data management accessible to non-technical users.
  • The AI-driven database system uses large language models (LLMs) like GPT-4 and reinforcement learning to automate core database functions, such as schema generation and natural language querying.

Statistics:

  • 2 students from different institutions collaborated on the INTED project, "AI-Powered Customer Support for Academic Counseling and Career Guidance".
  • The AI-driven database system tested achieved a 90% accuracy rate in responding to user questions in plain language.
  • The system improved speed and accuracy by 50% and adapted automatically to changing needs.
  • AI tools can provide scalable, personalized, and around-the-clock guidance to students, with potential applications in large educational institutions where counselor-to-student ratios are imbalanced (as high as 1 counselor per 500 students in some cases).

Sources:

  • Pace University news release:

Mary Tedeschi, professor at Pace University's Seidenberg School of Computer Science and Information Systems

INTED 2025

EDULEARN 2025

GPT-4

Reinforcement Learning

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