Session 4- Thursday, February 19, 2026 @ 12:15 - 1:15pm

This session introduces university faculty to essential principles of AI literacy and digital privacy. Participants will explore how AI tools influence teaching and learning, including opportunities for enhancing clarity, feedback, and accessibility, as well as challenges such as misinformation, bias, and academic integrity concerns. The session also provides practical guidance on protecting student data, understanding privacy risks, and setting clear expectations for responsible AI use in the classroom. Faculty will leave with actionable strategies to integrate AI effectively while maintaining ethical and privacy-conscious learning environments.

This session will be held in-person in room 302 at Penn State Lehigh Valley.

This presenters will be Pedro Robles, Assistant Teaching Professor of Cyber Analytics and Operations and Rifat Sabbir Mansur, Assistant Teaching Professor, IST

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Dr. Pedro Robles, Assistant Teaching Professor of Cyber Analytics and Operations

Credit: Penn State

Dr. Pedro Robles is an Assistant Teaching Professor of Cyber Analytics and Operations whose work focuses on the intersection of artificial intelligence, cybersecurity, and public policy. His research examines AI governance, cybersecurity strategy, and policy diffusion across state and international environments, with an emphasis on regulatory frameworks and emerging technologies. Dr. Robles’ scholarship bridges technical and policy domains, contributing to a deeper understanding of how governments develop, regulate, and implement advanced technologies in the public sector.

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Rifat Sabbir Mansur, Ph.D.

Credit: Penn State

Dr. Rifat Sabbir Mansur is an Assistant Professor of Teaching in the College of Information Sciences and Technology (IST) at Penn State Lehigh Valley. His research focuses on Artificial Intelligence in Education (AIED), particularly investigating how innovative assessment and feedback mechanisms can improve students' software development and testing skills. With expertise spanning Digital Education (DE), Software Engineering (SE), and Human-Computer Interaction (HCI), Dr. Mansur explores the intersection of automated grading systems, mutation testing, and self-regulated learning to enhance programming education. Prior to joining Penn State, he earned his Ph.D. in Computer Science from Virginia Tech, where his dissertation examined how students debug code and develop testing competencies. His work has been published in premier computing education venues including SIGCSE, IEEE, CHI, and CSCW. Dr. Mansur brings valuable industry experience from working at Meta, where he developed ML-based systems for performance monitoring and regression detection, complementing his commitment to bridging theory and practice in technology education.