Fengfeng Ke

Dr. Fengfeng Ke is Clark Leadership Chair Professor in the College of Education at University of Maryland, College Park. Her research focuses on the design and study of technology-driven personalized and enactive learning systems, with an emphasis on mathematics, science, and neurodiversity education. She is particularly interested in exploring the dynamics of human-AI collaboration in the development and implementation of innovative learning systems that prepare future professionals.

Her work has received funding from the National Science Foundation, the Spencer Foundation, the Department of Education, and the MacArthur Foundation.

Rosalyn Shin

Rosalyn is a first year PhD student in Technology, Learning, and Leadership (TLL) program at University of Maryland, College Park. Her main research interest is on how AI should be used to enhance personalized learning experiences and improve educational outcomes. She works on developing AI-integrated learning and teaching technology that provides equity-oriented STEM education for students of different backgrounds and abilities.

Meiyu (Emily) Li

Meiyu is a PhD student in Information Studies at the University of Maryland, College Park, and has a master's degree in Data Science from New York University. She develops machine learning and natural language processing methods to better understand teaching and learning, with a particular interest in building computational tools that support educators, analyze classroom interactions, and improve educational practice.

Xiaoxue Zhou

Xiaoxue Zhou is a doctoral candidate in the Technology, Learning, and Leadership (TLL) program at the University of Maryland, College Park. Her research focuses on the technology-enhanced learning environments design, leveraging data mining of collaborative learning behaviors and applying artificial intelligence to support personalized knowledge acquisition.

Her broader interests include learning technology governance, AI-driven personalization, and immersive simulations as tools for human-AI-augmented learning.

Nuodi Zhang

Nuodi is a PhD candidate in Instructional Systems and Learning Technologies at Florida State University. Her research investigates the design and use of educational technologies, including artificial intelligence, games, and simulations, to foster accessible, responsive, and adaptive learning experiences. With an emphasis on ecological and process-oriented perspectives, her work seeks to advance understanding of how teachers and diverse learners engage in STEM education.

Chaewon Kim

Chaewon is a PhD candidate in Instructional Systems and Learning Technologies at Florida State University. Her research investigates the design, development, and evaluation of learning experiences at the intersection of emerging technologies and human well-being.

Her work includes implementing educational escape rooms for nursing education, developing a digital game for promoting healthy eating habits among young adults, and leveraging artificial intelligence and virtual reality to support individuals with neurodiversity in rural areas.