Encourages students to think critically.
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Xiaoming Zhai, Ph.D., serves as Associate Professor in Science Education and the Institute for Artificial Intelligence, with courtesy appointments in Computer Science and Statistics, within the Department of Mathematics, Science, and Social Studies Education at the University of Georgia's Mary Frances Early College of Education. He earned his Ph.D. in Curriculum and Instruction (physics) from Beijing Normal University in 2017, M.Ed. in Curriculum and Instruction in Physics from the same university in 2012, and B.S. in Physics from Shandong Normal University in 2005. Before entering academia, Zhai taught physics at Zibo No. 1 Middle School from 2005 to 2014. His postdoctoral research was conducted at Stanford University's Laboratory of Educational Assessment, Research, and InnovatioN (LEARN) from 2017 to 2018. Subsequently, he held positions as Visiting Scholar and Research Specialist at the University of Illinois at Chicago (2018), Research Associate at Michigan State University's CREATE for STEM Institute (2019-2020), and joined the University of Georgia as Assistant Professor in 2020, advancing to Associate Professor.
As Director of the AI4STEM Education Center and Principal Investigator for the National Center of Generative AI for Uplifting STEM+C Education (National GENIUS Center), funded by a $10 million NSF grant, Zhai leads interdisciplinary efforts in AI for STEM education. His research interests encompass AI/machine learning-based innovative assessment practices in science, learning progressions, mobile learning in science, and science teacher education and career motivation. Notable awards include the Humboldt Research Fellowship for Experienced Researchers (2022), Sarah H. Moss Fellowship (2022), NAEd/Spencer Research Development Award (2021), AERA SIG TACTL Early Career Scholar Award (2021), and Jhumki Basu Scholar Award (2020). His influential publications feature "Assessing computational thinking: A systematic review of empirical studies" (Computers & Education, 2020), "Applying machine learning in science assessment: A systematic review" (Studies in Science Education, 2020), "ChatGPT for next generation science learning" (XRDS, 2023), and "Fine-tuning ChatGPT for automatic scoring" (Computers and Education: Artificial Intelligence, 2024). Zhai contributes editorially to journals such as Journal of Research in Science Teaching and Journal of Science Education and Technology, co-founded the RAISE Research Interest Group of NARST, and chairs NARST Strand 1 on Science Learning.
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