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Beyer Distinguished Lecture Series

Responsible and Grounded AI for STEM Education

Speaker
Arun Srinivasa
Date
Location
CBB 118; Classroom & Business Building
Abstract

There has been a lot of press about the effect of AI on the process of STEM education in general and developing competences in students. There have been many novel ideas about how to leverage AI for helping students perform better; there are equally deep concerns that students are misusing them n ways that are eliminating their critical thinking abilities and core cognitive competencies . There is no doubt that Large Language Models (LLMs) are already having a huge impact on what, whom and why we teach. At TAMU, we have been working on the use of AI for education well before LLMs were around. I will describe our experiments with early automated grading systems, findings on how well LLMs perform various tasks in STEM education and some guidelines that we follow for using AI responsibly for enhancing student education. In particular we will focus on two items: How AI can be used to enable faculty to practice good pedagogy easily and how it can be used to remove student frustration but not their effort. I will end with a demo of a opensource resources for context rich problems in mechanics and a AI portal (encando.com) that was created by my former PhD student Dr. Rujun Gao, that we are currently testing with classes across the Texas A&M College of Engineering.

About the speaker
Dr. Arun Srinivasa is the Associate Dean for Student Success in the College of Engineering at Texas A&M University and holds the J.N. Reddy Chair in Applied Mechanics. He previously served as Associate Department Head of Mechanical Engineering. His research focuses on simulation and optimization of fracture, fatigue, materials processing, impact dynamics, nonlocal and Cosserat theories, biomechanics, and continuum thermodynamics. He has published over 150 peer-reviewed journal papers, three books, and numerous articles on engineering education.
His educational interests include the incorporation of technology into education . He was Co-PI and director for the NSF RED (Revolutionizing Engineering Departments) Grant for the Department of Mechanical Engineering to create a community of practice focused on continuous innovation in teaching.
He has received numerous honors, including the 2025 Ralph Coates Roe Award (ASEE), the 2021 Ben Sparks Medal (ASME), the 2019 Worcester Reed Warner Medal (ASME), and the 2018 Archie Higdon Distinguished Educator Award (ASEE). At Texas A&M, his awards include the 2023 University Professorship for Undergraduate Teaching Excellence, the Association of Former Students Distinguished Achievement Award, the BP Award for Teaching Excellence, and the 2024 ASME Best Teacher Award from the student chapter. He has coauthored over 150 publications (including many in Engineering education), and 4 books.