ECE Speaker Series: Sidharth Jaggi

Title: Super-charging Flipped Classrooms: A Systematic Market-Driven Framework to Forge Communities of Learning

Abstract:

As instructors we often bemoan the fact that many students focus exclusively on grades, sometimes to the detriment of actual learning. I posit that at least part of the problem lies in the market-style reward structure we instantiate when designing assessment structures, with scarce resources (high grades) being offered to students in exchange for high quality work (assignments, exams). Students, being on the whole rational actors (despite some claims to the contrary), then tailor behaviour to capture the marginal grades.

Perhaps a key insight is that one way out of this is to carefully design market-style incentives coupled with appropriate graded learning activities to create virtuous cycles of positive peer-interaction behaviours among students, and create true communities of learning. At least to some extent altruism/community norms can supplant mercenary market incentives, leading to powerful peer-based learning.

In this talk I'll walk through a case-study of a freshman engineering mathematics class I've taught/am teaching in flipped format. I'll give examples of such incentive mechanisms coupled with T&L activities and learning outcomes, and a framework to structure these around. I'll also highlight some remarkable student learning outcomes.

I aim for this to be an informal talk, and hope there will be an interactive discussion with audience members about their own T&L ideas and experiences.

Biography:

Prof. Sidharth Jaggi has been with the Chinese University of Hong Kong since 2007, where is currently an Associate Professor in the Department of Information Engineering.

He is a recipient of various Department, Faculty, and University-wide teaching awards, and also a finalist for the 2019 Hong Kong-wide UGC Teaching Award. He has helped set up a community of practice at CUHK, given multiple talks and written academic papers on T&L pedagogy, and has multiple T&L grants/projects (including one with MIT). Some of his innovations in pedagogy have attracted media attention.

In addition, his mathematical research interests lie at the intersection of network information theory, coding theory, and algorithms. His research group thus (somewhat unwillingly) calls itself the CAN-DO-IT team (Codes, Algorithms, Networks: Design and Optimization for Information Theory). He is particularly known for the eponymous “Jaggi-Sanders” Algorithm, for his work on network coding, group testing, covert communication, and adversarial channels.