Lisa Yan

Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement.

Her academic credentials include:

• PhD in Electrical Engineering from Stanford University (2019)
• MS in Electrical Engineering from Stanford University (2015)
• BS in Electrical Engineering and Computer Science from UC Berkeley (2013)

Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education.

Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses.

She received recognition through:

• The Faculty Award for Outstanding Mentorship of GSIs (2024)

Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations.

Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.