Katherine Xu

Beyond research and development, I have a proven track record of designing and scaling high-impact learning experiences for large, diverse student populations. My approach to teaching is rooted in data-driven iteration and user-centered design.

• Curriculum Architecture at Scale: Designed and iterated end-to-end learning experiences for a 1,300+ student user base across Computer Science and Language subjects, maintaining a high satisfaction rate through rigorous instructional standards.

• Data-Driven Iteration: Identified critical learner pain points by analyzing performance data and student feedback. This led to the redesign of 25+ distinct curricula, specifically optimized to improve engagement, conceptual comprehension, and long-term retention.

• Quality Assurance & Mentorship: Served as a Subject Interviewer, evaluating prospective instructors on teaching quality and alignment with pedagogical standards to ensure consistency across the instructional team.

My published work focuses on the integration of emerging technologies into educational frameworks, specifically exploring how AI-driven dialogue can enhance immersive learning environments.

Xu, H. (2022). A Future Direction for Virtual Reality Language Learning Using Dialogue Generation Systems. Journal of Education, Humanities and Social Sciences, 2, 17-23.

• Core Thesis: This paper investigates the integration of Large Language Models (LLMs) and dialogue generation systems into Virtual Reality (VR) to create high-fidelity, naturalistic language-learning simulations.

• Strategic Impact: At a time when VR was often treated as a visual-only medium, this research identified and discussed the critical possibility of embedding LLMs into multimodal technologies. It argues that the next leap in immersive tech is not just visual presence, but cognitive authenticity—using AI to provide the social and conversational depth necessary for true experiential learning.