Xinying Hou is a PhD candidate at the School of Information, University of Michigan. She designs, develops, and evaluates AI-powered techniques to support learning and assessment, particularly in computing and STEM education. Her PhD research combines AI with active learning to enhance students' skills, such as problem-solving and comprehension, while preventing AI from becoming a shortcut to final answers. She achieves this by providing engaging, personalized, and hands-on support for novice programmers as they learn to code. Her work has been published in top-tier conferences and journals in AI in Education, Computing Education, and Educational Technology, receiving several awards. She received her Master's in Educational Technology and Applied Learning Science (METALS) from Carnegie Mellon University. She has also worked as a Research Intern at the Educational Testing Service Research Institute.

Pronouns

she/her/hers

Areas of interest

AI in Education, Educational Technology, AI Literacy, Computing Education

Education

METALS, Human-Computer Interaction Institute, Carnegie Mellon University, 2020