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Computer Science Department Colloquium

Rethinking Curriculum Design for a Scalable CS Education


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Thursday, January 13, 2022, 11:00am


Speaker: Prof. Andy Gunawardena


Prof. Andy Gunawardena is an Associate Teaching Professor of Computer Science at Rutgers University. Prior to joining Rutgers in 2018, he served as an Associate Teaching Professor of Computer Science at Carnegie Mellon University (CMU) from 1998-2013 and as a Lecturer in Computer Science at Princeton University from 2013-2018. A dedicated CS educator and an evangelist for technology in education, he has been a PI and Co-PI of multiple grants from National Science Foundation, Hewlett Packard, Microsoft, Gates Foundation and Qatar foundation to research, build, deploy technological infrastructures to support student learning and measure their impact. He co-led the CMU’s multi-million-dollar measuring learning initiative in 2010 and is a co-founder of Classroom Salon and cubits.ai platforms that have been widely used by instructors and students worldwide. He holds 3 patents (CMU, Princeton) and has co-authored 2 textbooks in Computational Linear Algebra published by Springer-Verlag (1998) and Cengage (2003).

Location : Via Zoom

Event Type: Computer Science Department Colloquium

Abstract: Number of students taking CS courses have increased dramatically in recent times. At the same time, the availability of human resources to manage CS courses have decreased. The traditional teaching methods have not changed, and student overall educational experiences seem to have diminished over time and continue to do so. Today, instructors hardly understand the individual needs of the students they are responsible for. There are also significant disruptive pressures in higher education due to prevalence of online content and opportunities. Attracting and retaining women and under-represented groups continue to be a challenge. Students demand that instructors teach what is relevant for them to get jobs in industry and/or to pursue higher education opportunities. Addressing these issues require significant efforts in course innovation and long-term dedication. In this talk, we will address the efforts to revamp 3 introductory CS courses at Rutgers (CS 111, CS 112, CS 205) as well as challenges in designing, implementing, and delivering the popular CS 439 Introduction to Data Science course at Rutgers. We will argue that it is important to rethink what we teach, how we teach it, and how we measure student outcomes. We will also argue for the need to centralize the management of large enrollment courses and the need to create more data-driven measuring instruments to help scale student learning in large courses. Finally, we discuss some initial efforts to increase outreach into NJ communities colleges (CC) and provide better transfer opportunities for a diverse group of students from CCs.


Rutgers University School of Arts and Sciences

Contact  Host: Dr. Matthew Stone

Meeting Recording:


Access Passcode: W8RTR&6R