Kexin “Bella” Yang actively conducts K-12 ed-tech research, and has expertise in applying human-computer interaction methods in learning sciences and the edtech industry.

Her research aims to design data-driven human-AI algorithmic systems for smart classrooms of the future, that 1) respect stakeholders’ (teachers and students) boundaries, agency, and preferences, 2) augment teachers’ abilities to distribute their limited attention to where it is needed the most, and 3) achieve effective, self-paced personalized learning that suit students’ individual needs.

She has worked on and broadly interested in social computing (e.g., crowdsourcing), XR, robotics, NLP, and their application in education.

She is well versed in qualitative, quantitative, and human-centered design research methods, including surveys, interviews, prototyping, focus groups, participatory design, usability testing, think-aloud protocol, field testing, AB testing, log-data analysis, statistical modeling and experiment design.