Program
2026 keynote speakers
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Dr. Bonnie J. Dunbar
Dr. Bonnie J. Dunbar, a retired NASA astronaut, engineer, and educator, is currently associated with Texas A&M Engineering as the John and Bea Slattery Chair in the Department of Aerospace Engineering. Her laboratory, the Aerospace Human Systems Laboratory (AHSL), focuses on research connected to human space systems, such as spacesuits and habitats; the physiological effects of partial gravity; and the study of partial gravity fluid physics as they pertain to space exploration engineering. She leads the Systems, Design and Human Integration (SDHI) group within the Aerospace Engineering Department, and she is overseeing the development and installation of a human-rated short-arm research centrifuge, which was previously operated by NASA for artificial gravity research supporting human missions to the Moon and Mars.
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The proliferation of artificial intelligence (AI) tools and large language models (LLMs) has sparked dramatic changes to the landscape of post-secondary education resulting in new opportunities (and obligations) to re-evaluate norms for teaching and learning. This presentation includes a brief overview with perspective about rethinking assessment practices—i.e., how student learning is evaluated—during a period of such rapidly evolving technology. The session then transitions to sharing greater detail about ongoing research sponsored by the National Science Foundation, Penn State’s Center for Socially Responsible Artificial Intelligence, and a strategic partnership between Penn State University and the University of Auckland (NZ), which seeks to develop LLM and AI-based tools intended to amplify instructor efforts to provide timely, personalized feedback to open-ended questions during class, especially for use in large classes (hundreds of students) at scales for which the logistics of doing so would be either untenable or impossible without a teacher-AI partnership. To this end, we will also discuss how our team has approached evaluating performance of the tools we develop in order to build trust and confidence that they make a responsible contribution to the teaching team.
bio-beckman
Matthew Beckman
Matthew Beckman is an Associate Research Professor of Statistics at Penn State and Executive Director of the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE; www.causeweb.org).
He earned his PhD in Statistics Education and MS in Statistics from the University of Minnesota, and he earned a BS in Mathematics from Penn State University.
Beckman's research interests include Statistics & Data Science Education, especially post-secondary teaching, learning, and assessment. For example, he is currently PI of Project CLASSIFIES (NSF Award# 2236150) which seeks to develop and investigate tools that leverage Natural Language Processing to assist STEM instructors in large-enrollment classes with providing student feedback on short-answer tasks.
Prior to joining Penn State, Beckman worked in the medical technology sector as a Sr. Statistician at Medtronic, and a Sr. Biostatistician at Nonin Medical.
Agenda at-a-glance (subject to change)
Thursday, March 5
7:00am - 5:00pm Registration
8:00am - 2:30pm MyLab Certification Workshops
12:00pm - 4:30pm Pre-conference Session
5:00pm - 7:00pm ICTCM Welcome Celebration
Friday, March 6
7:00am - 4:00pm Registration
8:00am - 9:15am Breakfast, Welcome & Keynote Address
9:00am - 4:00pm Innovation Lab
9:30am - 4:15pm Sessions/Mini-Courses
Saturday, March 7
7:00am - 12:00pm Registration
8:00am - 9:00am Breakfast & Keynote Address with Matthew Beckman
9:00am - 1:00pm Innovation Lab
9:30am - 2:00pm Sessions/Mini-Courses
MyLab Math and MyLab Statistics Certification
Join Pearson Faculty Advisors and Advocates on Thursday, March 5th for a full day of in-depth MyLab training. The MyLab Math and MyLab Statistics Certification is an intentionally crafted learning experience designed by the Pearson Math and Stats team.