Advancing AI in Science Education (AASE)

Linn is the Evelyn Lois Corey Professor of Instructional Science, specializing in science and technology, in the School of Education at the University of California, Berkeley. She is a member of the National Academy of Education and a Fellow of the American Association for the Advancement of Science (AAAS), the American Psychological Association, the Association for Psychological Science, and the International Society of the Learning Sciences (ISLS). She has served as president of the ISLS, chair of the AAAS Education Section, and on the boards of the AAAS, the Educational Testing Service Graduate Record Examination, the McDonnell Foundation Cognitive Studies in Education Practice, and the National Science Foundation Education and Human Resources Directorate. Her awards include the National Association for Research in Science Teaching Award for Lifelong Distinguished Contributions to Science Education, the American Educational Research Association Willystine Goodsell Award, and the Council of Scientific Society Presidents’ first award for Excellence in Educational Research. Her books include “Computers, Teachers, Peers” (2000), “Internet Environments for Science Education” (2004), “Designing Coherent Science Education” (2008), “WISE Science” (2009), and “Science Teaching and Learning: Taking Advantage of Technology to Promote Knowledge Integration” (2011). She chairs the Technology, Education—Connections (TEC) series for Teachers College Press.

Lee is a professor in the Steinhardt School of Culture, Education, and Human Development at New York University. She is widely known for advancing research, policy, and practice that simultaneously promote science and language learning for all students, particularly multilingual learners. Lee was a member of the NGSS writing team and served as leader of the NGSS Diversity and Equity Team. She also was a member of the Steering Committee for the Understanding Language Initiative at Stanford University. Her research involves integrating science, language, and computational thinking with a focus on multilingual learners. Her latest work addresses justice-centered STEM education with multilingual learners by integrating multiple STEM subjects, including data science and computer science, to address pressing societal challenges using the case of the COVID-19 pandemic. Lee is the recipient of many honors, awards, and fellowships, including the Distinguished Contributions to Science Education through Research Award, National Association for Research in Science Teaching, 2023; Honorary doctor of humanities degree recipient and keynote speaker at the Baccalaureate Commencement Ceremony, Michigan State University, 2022; National Academy of Education member, 2022; American Association for the Advancement of Science Fellow: Section Q Education, 2021; American Educational Research Association: Exemplary Contributions to Practice-Engaged Research Award, 2021; National Science Teaching Association: NSTA Distinguished Service to Science Education Award, 2020; Division K Innovations in Research on Equity and Social Justice in Teacher Education Award, 2019; and AERA Fellow, 2009.

Juan-Carlos Aguilar is the director of innovative programs and research in the Office of Teaching and Learning at the Georgia Department of Education. Aguilar contributed to the advancement of science education both at the state and national level.

Haudek is an associate professor in the Department of Biochemistry and Molecular Biology at Michigan State University, with a joint appointment at the CREATE for STEM Institute. He earned his Ph.D. in biochemistry and focuses on discipline-based education research. Haudek’s research centers on improving college students’ understanding and application of foundational concepts in chemistry and biology, as well as enhancing the use of formative assessments in undergraduate STEM education. His work integrates artificial intelligence approaches to develop “knowledge-in-use” science assessments and evaluate student writing and models. His research group employs these AI-driven methods to identify emergent ideas in student writing and create models that automatically assess student responses, with the aim to support students in solving complex scientific problems. Haudek is also interested in how AI tools can be applied equitably to diverse student responses, while tailoring individualized supports to reflect students’ unique backgrounds.

King is an associate professor of science education at Georgia State University. Her scholarly work focuses on advancing Black girls in STEM education, community-based STEM programs, and the role of curriculum in fostering equity in science teaching and learning. King is a recipient of the 2023 National Science Foundation Alan T. Waterman Award—the nation’s highest honor for early career scientists and engineers. She is the first educator to receive this recognition. King is also an NSF Early CAREER Award (#1943285) recipient whose research challenges the capitalist agenda for encouraging girls’ involvement in STEM. She elevates the identities and brilliance of Black girls in her scholarship, programs, and grant projects. In addition, King serves as the principal investigator of an NSF Noyce project (#1852889) seeking to diversify the STEM teaching workforce. King is the founder and executive director of I AM STEM, LLC and partners with community-based organizations to provide Black and Brown children with access to comprehensive academic summer enrichment programs that embrace their cultural experiences while also preparing them to become productive and critically-conscious citizens. Her work is published in the Journal of Research in Science Teaching, Science Education, Journal of Multicultural Affairs, Journal of Science Teacher Education, The Science Teacher, and Teaching and Teacher Education.

Kubsch is an sssistant professor of physics education research at Freie Universität Berlin and author of the textbook “Applying Machine Learning in Science Education Research: When, How, and Why?”. Two foci of his work are the role of AI techniques such as machine learning (ML) and natural language processing (NLP) to better understand and support science learning in digitally enriched learning environments and the usage of such methods as ways to augment science education research methodology. Overall, he is passionate about using AI in a productive and equitable way to advance science education research.

Lee is an assistant professor in the Natural Sciences and Science Education Group at the National Institute of Education (NIE), Nanyang Technological University (NTU), Singapore. He earned his Ph.D. in science education from Seoul National University in South Korea in 2023, where he also received his B.Sc. in chemistry education and B.Sc. in computer science and engineering in 2016. Before joining NTU, he worked as a postdoctoral research associate at the AI4STEM Education Center at UGA from 2023 to 2024. His recent research focuses on integrating AI into science education, encompassing automatic assessment, human-AI collaboration in learning, and lab safety management. His previous research publications have covered various topics, including the history and philosophy of science education, curriculum studies, blended learning, and electrochemistry. Through the interdisciplinarity enabled by AI, he aims to establish multimodal science learning to fulfill whole-person science education.

Liu is the research director of the K–12 research team at ETS Research Institute and an adjunct professor at the University of Pennsylvania. She holds a Ph.D. in educational psychology with a specialization in learning sciences and educational technology from Rutgers University. Liu’s research spans science education, assessment, educational technology, and skills development. She has led numerous federally-funded projects aimed at advancing STEM education through innovations such as learning progressions, AI-supported assessments, and virtual laboratories. She has published over 70 peer-reviewed articles in leading academic journals, books and conference proceedings, covering a wide range of topics including science education, assessment methodologies, the role of technology in learning, and the development of skills crucial for students’ success in higher education and the workforce. In addition to her research leadership, Liu is instrumental in managing large-scale operational programs at ETS, including the California state assessment initiatives and the National Assessment of Educational Progress (NAEP) in science and mathematics. She is a member of the editorial board of Instructional Science and has served as a reviewer for multiple international conferences, journals, and NSF merit reviews.

Professor Liu is a professor of STEM education at the University of Macau. Liu obtained his master’s degree from East China Normal University in 1986 and his Ph.D. from the University of British Columbia in 1993. Prior to joining the University of Macau, he taught high school chemistry in China, was a research associate at the China National Institute for Educational Research (currently Chinese Academy of Education), a tenured faculty member at St. Francis Xavier University and University of Prince Edward Island, both in Canada, and most recently a SUNY Distinguished Professor of Science Education in the Graduate School of Education, University at Buffalo, State University of New York. Liu’s research interests include measurement and evaluation in STEM education, student conceptual progression of cross-cutting concepts (i.e., matter and energy), and student and teacher STEM identity measurement and development. Liu is a Fellow of the American Association for the Advancement of Science, a recipient of the Exceptional Scholars Sustained Achievement Award, University at Buffalo, and a guest/honorary professor at a few universities in China.

Mikeska is a managing principal research scientist in the ETS Research Institute. She earned a Ph.D. in curriculum, teaching, and educational policy (emphasis in science education) from Michigan State University in 2010. Her research focuses on four related areas: (1) designing, developing, and conducting validation studies on assessments of content knowledge for teaching (CKT) science; (2) examining and understanding validity issues associated with measures designed to assess science teachers’ instructional quality, including observational measures, value-added measures, student surveys, and performance-based tasks; (3) extending and studying the use of these knowledge and instructional practice measures of science teaching quality as summative assessment tools for licensure purposes and as formative assessment tools integrated within teacher education and professional development contexts; and (4) examining how artificial intelligence can be used to support science teacher learning of key teaching competencies. She has been the principal investigator on numerous National Science Foundation research projects (#1621344, #1813254, #2037983, and #2032179) and has served on the editorial review boards of the Journal of Research in Science Teaching, the Journal of Science Teacher Education, Innovations in Science Teacher Education, and the American Educational Research Journal, where she received the Outstanding Reviewer Award in 2018. Mikeska facilitated a working conference in 2018 on the role of simulations in K-12 science and mathematics teacher education and served on the planning committee for the NSF DRK-12 2021 principal investigator conference.

Nehm, is PI of the BER Lab, professor of ecology and evolution, and a member of the graduate program in science education at The State University of New York, Stonybrook. His major awards include a CAREER award from the National Science Foundation, a student mentoring award from CUNY, and a teaching award from Berkeley. He was named an Education Fellow in the Life Sciences by the U.S. National Academy of Sciences. Nehm has served in academic leadership roles nationally and internationally, including as editor-in-chief of the journal Evolution: Evolution Education and Outreach, associate editor of Science & Education, associate editor of the Journal of Research in Science Teaching, editor of CBE-Life Sciences Education, and a board member of several other academic journals. He has been a frequent invited speaker nationally and internationally, including at the U.S. National Academy of Sciences, as a James Moore Lecturer at the Society for Integrative and Comparative Biology, and as a keynote speaker in several countries (e.g., Germany, Sweden, China, Chile). He has served on the research advisory boards of many federally funded science education projects, NSF’s Committee of Visitors, and many NSF panels as chair. His research findings have been featured in The New Republic, Science Magazine’s Editor’s Choice, CBS News, and many other outlets.

Knut Neumann is professor of physics education and director of the Department of Physics Education at the Leibniz-Institute for Science and Mathematics Education (IPN) in Kiel, Germany. He has considerable expertise in the development of assessments. He was PI on several grants assessing students’ progression in understanding core science concepts. He also served on the NRC Committee on Developing Assessments of Science Proficiency in K-12. More recently, Neumann explored the potential of using AI techniques for continuously monitoring students progression in developing competence in science based on the artifacts that students produce as they learn with digital technologies, as well as for providing more individualized learning opportunities.

Gao’s research focuses on AI in science education. She leverages AI techniques to design and build adaptive learning systems, making personalized learning scenarized, intelligent, and scalable. She also uses educational data mining and machine learning techniques to identify students’ behavioral and complex cognitive patterns (e.g., problem solving, inquiry). Through these efforts, she aims to enhance the effectiveness and inclusivity of science education practices.

Xiaoming Zhai, PI, director of AI4STM Education Center, and associate professor of science education and artificial intelligence at UGA, has extensive experience in applying AI and machines to facilitate science teaching and learning. He is PI and co-PI of several NSF, NIH, and NAEd/Spencer projects. He is a recipient of the Humboldt Research Fellowship (Germany), Sarah H. Moss Fellowship, and AERA SIG Early Career Scholar Award. He is the founding chair of the research interest group of NARST, Research in AI-involved Science Education (RAISE), he chaired the International Conference of AI-Based Assessment in STEM, and edited the “Special Issue: Applying Machine Learning in Science Assessment.” He will oversee the project and co-edit the conference proceeding book.

Kent Crippen, co-PI, is a professor of STEM education in the School of Teaching and Learning at the University of Florida, a Fellow of the American Association for the Advancement of Science, and editor-in-chief of the Journal of Science Education and Technology. His expertise—especially in chemistry education—involves designing and evaluating learning environments and professional development experiences for K-12 teachers. In addition to NSF and NIH-funded research translating new and emerging science into instructional materials and programs, Crippen has served as PI on multiple state-funded professional development projects for teachers. He is the founding co-chair of Research in AI-involved Science Education (RAISE), a NARST Research Interest Group. He will work with the meeting facilitator to execute the facilitation plan based on the project’s goals and co-edit the conference proceeding book.