Abstract: Over the past decade, undergraduate Computer Science (CS) programs across the United States have experienced an explosive growth in enrollment as computational skills have proven increasingly important across many disciplines and the workforce at large. Motivated by this unprecedented student demand, the CS program at the University of California, Berkeley has tripled the size of its graduating class in five years. The first two introductory courses for majors, each taught by one faculty instructor and several hundred student teachers, combine to serve nearly 2,900 students per term. This talk will present three solutions that have enabled effective teaching, delivery, and management of these large-scale CS courses: (a) the development of autograder infrastructure and online platforms to provide instant feedback and minimize manual grading; (b) the subsequent optimization of staffing strategies and course policies to increase contact hours and personalize student learning; and (c) the expansion of an undergraduate teaching assistant (TA) training pipeline to meet the increased demand for student teachers. These strategies have enabled the delivery of both introductory and advanced courses to over 800 students while receiving among the highest student evaluations of teaching in department history.

Short Bio: Kevin Lin is a master’s candidate in the Electrical Engineering and Computer Sciences department at UC Berkeley. He coordinates the teaching and development of large-scale, introductory undergraduate CS courses which, in total, support enrollments of over 3,500 students each year. His research focuses on computer science education with a particular emphasis on methods for broadening participation and retention in classrooms of all sizes.