2023 ASEE Annual Conference & Exposition

One of These Things Is Not Like the Others... Machines Can Learn to Classify Too (Resource Exchange)

Presented at Pre-College Engineering Education Division (PCEE) Technical Session 12: Resource Exchange

Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are highly popularized as tools to solve many problems in finance, computer security, natural language processing, and image processing. The use of these in cancer research has potential to reduce diagnostic time, improve detection, and potentially inform treatment. There are opportunities to scaffold learning with hands-on activities in the context of a societal problem to strengthen interest and persistence in STEM careers. Within ML, classification can be distilled to identification of features that are similar or different in a series of pictures. The game, “One of These Things (Is Not Like the Others)” popularized by Sesame Street, can be used to introduce students to this complex algorithm.

Authors

Dr. Stephany Coffman-Wolph Ohio Northern University [biography]

Dr. Stephany Coffman-Wolph is an Assistant Professor at Ohio Northern University in the Department of Electrical, Computer Engineering, and Computer Science (ECCS). Research interests include: Artificial Intelligence, Fuzzy Logic, Game Theory, Teaching Computer Science to First-Year, K-12 Outreach, and Increasing Diversity in STEM.
Dr. Marcia Pool http://orcid.org/0000-0002-2813-4217 University of Illinois at Urbana - Champaign [biography]

Dr. Marcia (“Marci”) Pool is the Assistant Director for Education at the Cancer Center at Illinois and a Teaching Associate Professor in Bioengineering. She holds a Ph.D. in Biomedical Engineering, has served for sixteen years as teaching faculty/staff in biomedical/bioengineering and nine years in departmental/institute educational administration, and is an ABET program evaluator for Bioengineering/Biomedical Engineering. She focuses on identifying and evaluating mechanisms to enhance the educational experience and develop students into engineers and researchers. Her work includes interventions to enhance training for high school students, undergraduate students, and predoctoral (graduate students) and postdoctoral trainees through training programs such as NIH T32s. These programs include curricular, extracurricular, and professional and career development components with required evaluation and tracking of student participants.
Dr. Kimberlyn Gray West Virginia University Institute of Technology [biography]

Dr. Kimberlyn Gray is an Associate Professor at West Virginia University Institute of Technology in the department of Chemical Engineering.
Dr. John T. Hird http://orcid.org/0000-0002-8491-4170 West Virginia University Institute of Technology

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