Abstract: Today’s education has numerous challenges. A lasting one is to integrate the teaching and learning of subjects in Science, Technology, Engineering and Mathematics (STEM), for students from kindergarten to college (K-16). Recent challenges include how to teach Computing and Artificial Intelligence (AI) in K-16. The breakthrough in generative AI, exemplified by chatGPT, raises concerns about the loss of jobs and what we should teach our next generation. Drawing from humanity's millennia of accumulated understanding of the mind and nature, Computing and AI do provide opportunities to address those challenges and concerns. Particularly, they offer some “universal language” and methodologies to unify a wide range of the knowledge and skills of STEM subjects including Computing and AI naturally, coherently, and explicitly. This perspective offers new STEM learning approaches which will enhance students' reasoning skills, addressing a current gap in generative AI and positioning the students better for the future job market. In conjunction with generative and logic-based AI, two pillars of AI, the strong structure of the knowledge of STEM subjects resulting from the new approaches is anticipated to lead to the development of powerful intelligent systems to assist students’ learning.

Short Bio: Dr. Yuanlin Zhang is an Associate Professor of Computer Science at Texas Tech University. He obtained his BEng degree and PhD in computer science from Nanjing University of Science and Technology and National University of Singapore. With a background in Knowledge Representation and Reasoning in Artificial Intelligence (AI), his current research focuses on how AI and Computing, as both theoretical and technological tools, may help students learn the STEM subjects including Computing and AI in an integrated manner. His work has been published in journals and conferences including AI journal, AAAI and IJCAI. He has also received awards including the AI journal classic paper award (2022). His research has been supported by various federal programs, including those of NSF and the Department of Education. Dr. Zhang has served on the program committees of conferences such as AAAI and IJCAI, and as a panelist for NSF programs.