For the high-flex option, register in advance. You will receive a confirmation email containing information about joining the meeting.

Title:
Computational Thinking for Engineers in the AI Era

Abstract:
Are you curious about how to assess students’ entry-level skills early and use that information to deliver targeted, scalable instruction in engineering classrooms? Are you looking for meaningful ways to evaluate student learning as evidence of effective teaching? If so, this interactive presentation is designed for you. We introduce the development and implementation of a computational thinking diagnostic that supports early differentiation and informs instructional decision-making across engineering curricula. In addition, we present a set of flexible educational interventions designed to teach coding concepts in any programming language, making them adaptable across courses, institutions, and class sizes. The presentation highlights the progression of core abilities and conceptual milestones involved in computational thinking development and demonstrates a practical model for teaching in classrooms of any size, from small seminars to large lecture-based courses.

Participants will be invited to reflect on how the diagnostic can be adapted and transferred to other engineering content areas, including artificial intelligence and machine learning. We further discuss the foundational AI/ML knowledge and skills all engineers should possess and how these competencies are rooted in computational thinking. Finally, the session addresses the psychological well-being of engineering students in the context of increasing reliance on generative AI tools such as ChatGPT.

Bio:
Dr. Noemi V. Mendoza Diaz is an Assistant Professor in the Technology Management Program (TCMG) in the College of Engineering at Texas A&M University, with a courtesy appointment in the College of Education. She is an Electronics and Communications Engineer with an M.S. in Telecommunications Engineering and earned her Ph.D. in Educational Administration and Human Resource Development. She completed a two-year postdoctoral appointment at the School of Engineering Education at Purdue University. Her research focuses on computer and engineering education, with particular emphasis on computational thinking, AI/ML training for all engineers, and the experiences of underrepresented populations in engineering, especially the Latinx community. She is a recipient of the ASEE Educational Research and Methods (ERM) Division Apprentice Faculty Award and has received two National Science Foundation awards through the Research in the Formation of Engineers program. Her NSF-funded work examines the enculturation of students into engineering and the development of computational thinking skills. She is currently extending this research to explore the psychological well-being of engineering students in the era of generative AI tools such as ChatGPT. Dr. Mendoza Diaz is an active member of ASEE and IEEE, regularly publishing in and attending national and international conferences. She serves on the Steering Committee for the Frontiers in Education Conference (ASEE–IEEE) and advises several student organizations, including TCMG, SHPE, and MAES.

Citation:
Mendoza Diaz, N. V., Yoon, S. Y., & Salvador, N. G. (2025). Digital Equity and Computational Thinking Privilege: The Case of First-Year Engineering and Computing Students’ Attitudes towards Artificial Intelligence. Computers and Education: Artificial Intelligence, 100495. https://doi.org/10.1016/j.caeai.2025.100495