2026 ASEE Annual Conference & Exposition

AI-Driven Climate Resilience Education: A Framework for Predictive Thinking in Engineering Classrooms

Presented at CIT Technical Session 4: Capacity Building, and Skill Development.

Engineering education often emphasizes design and analysis while giving limited attention to predictive and adaptive decision-making in response to climate change. As transportation systems face increasing weather-related disruptions, there is a growing need to prepare future engineers to reason about climate resilience using data-driven tools.
This work introduces the AI-Driven Climate Resilience Education (AICRE) framework, a pedagogical approach designed to support climate-resilient engineering decision-making through the use of artificial intelligence and real-world data. The framework was implemented as a work-in-progress instructional approach within an undergraduate engineering course focused on data-driven systems analysis. In this context, AI techniques serve as analytical tools to help students interpret climate-related data, anticipate system disruptions, and evaluate adaptive responses.
Students will engage in project-based learning activities using datasets from the Federal Aviation Administration and Open-Meteo Statistics to examine weather-induced disruptions in air transportation systems. Guided modules introduced students to predictive modeling concepts, including logistic regression and random forest methods, as a means of supporting climate-informed decision-making rather than as standalone technical outcomes. Evaluation methods will include pre- and post-activity surveys, reflective journals, and analysis of team project artifacts.
Preliminary observations from the ongoing implementation drawn from qualitative coding of student activity responses (N = 17), indicate considerable variation in student engagement across the framework's four components. Uncertainty communication about model limitations emerged broadly across the cohort, with 59% of students acknowledging prediction error or the conditional nature of model outputs without direct prompting. However, the predictive interpretation component which requires reasoning about future system behavior under changing climate conditions showed the lowest activation rate, with 47% of students producing no substantive response. These findings point to specific instructional refinements needed to support the full AICRE learning cycle in future implementations.

Authors

Mrs. Abiola Olayinka Ajala Mrs http://orcid.org/0009-0001-8848-1843 Morgan State University [biography]

Abiola Olayinka Ajala is an AI researcher for the National Airspace System (NAS) at Morgan State University, pursuing a Ph.D. in Electrical and Computer Systems Engineering with a focus on Data Science, Machine Learning, and AI. Currently working on a research on climate resilience and aviation security using AI-driven solutions. With a Master’s in Advanced Computing and a Bachelor’s in Computer Science, Abiola has expertise in data science, cybersecurity, networking, business analysis, and system administration. A member of ASEE,IEEE who is passionate about STEM education to introduce K1-12 students to computing/ engineering skills and digital literacy.
Blessing Isoyiza ADEIKA http://orcid.org/https://0009-0007-5600-8051 Morgan State University [biography]

Blessing ADEIKA is a graduate student at Morgan State University currently studying Advanced Computing. She has interest in teaching student basic concepts by adopting an Experiment-centric approach to it. She also is currently working towards being a Data Scientist - AI/ML Expert and hope to use her skills to prefer solutions in the Medical, Financial, Technology and any other Sector she sees a need to be filled/catered for.
Raj Bariya Morgan State University [biography]

Raj is currently completing is BS in Computer Science from Morgan State University and working as a undergraduate research assistant in DEPA lab within Morgan State University.
Samuel Sola Akosile Morgan State University [biography]

Samuel Akosile is a Ph.D. student in Sustainable Infrastructure and Resilience Engineering at Morgan State University, within the Department of Civil Engineering. He currently works as a Research Assistant, contributing to innovative studies in the field of civil infrastructure. His primary research area focuses on sustainable design for pavement systems, aiming to develop environmentally responsible, durable, and cost-effective solutions for modern transportation networks. Samuel’s work explores the integration of green materials, lifecycle assessment, and resilient engineering practices in pavement design. Through his research, he seeks to address key challenges in infrastructure sustainability while promoting long-term resilience in the face of climate change and increasing urban demands
Sarah Halleluyah Adeyemi Morgan State University [biography]

Sarah Halleluyah Adeyemi is a Master student in the Department of Bioinformatics at Morgan State University. She holds a B.Sc. in Microbiology from Mountain Top University, Nigeria. Her research interests focus on gene expression analysis, cardiovascular genomics, antimicrobial resistance, and the application of computational tools in biomedical research. She is also currently working towards being a Data Scientist.

Sarah has research experience from the Nigerian Institute of Medical Research, where she contributed to infectious disease diagnostics and antimicrobial studies. She also worked in the R&D division at FrieslandCampina WAMCO, gaining insight into food safety, quality control, and process validation. Currently, she serves as a graduate assistant on interdisciplinary research projects funded by NASA and ETA-STEM, supporting data analysis and science education initiatives.

She is a member of ASEE, IEEE, passionate about STEM education and is passionate about integrating bioinformatics and molecular biology to solve health-related challenges and promote inclusive scientific research.
Dr. Oludare Adegbola Owolabi P.E. Morgan State University [biography]

Dr. Oludare Owolabi, a professional engineer in Maryland, joined the Morgan State University faculty in 2010. He is the director of the Sustainable Infrastructure Development, Smart Innovation and Resilient Engineering Research Lab, Department of Civil Engineering at Morgan State University.
Dr. Kofi Nyarko Morgan State University [biography]

Dr. Kofi Nyarko is a Tenured Associate Professor in the Department of Electrical and Computer Engineering at Morgan State University. He also serves as Director of the Engineering Visualization Research Laboratory (EVRL). Under his direction, EVRL has acq
Dr. DeAnna Bailey Morgan State University [biography]

Dr. DeAnna Bailey is a faculty member of the Department of Electrical and Computer Engineering at Morgan State University. Dr. Bailey has an academic background in electrical engineering (B.S. in electrical engineering and Doctor of Engineering). She researches, develops and examines effective methods of teaching STEM to African American youth. At her university, she utilizes African-Centered methodology to teach electrical engineering concepts. She founded and co-founded various programs to increase African American participation in STEM by exposing urban African American youth to science, technology, engineering, art and mathematics (STEM) in ways that supports their interest, confidence and knowledge in STEM and affirms their cultural identity. Additionally, Dr. Bailey has partnered with local community organizations to create and implement camps focusing on leadership development, critical thinking skills, cultural education, and physical training. She has been a featured speaker at numerous conferences and workshops, including the National Academy of Sciences workshop on engaging Black men and women in engineering. Dr. Bailey aims to advance racial equity in STEM education by introducing innovative ideas, teaching techniques, and curricula to the engineering education research community, while also seeking to reconceptualize engineering for African American people.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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