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Inclusive Study Group Formation at Scale

On today’s show, Kyle speaks with Gireeja Ranade, a professor at the University of California at Berkeley. Gireeja works on various projects, from theoretical control to understanding misinformation spread. She is also passionate about teaching. Gireeja shares some insight on her research: Inclusive Study Group Formation at Scale.

It is critical that in large and diverse classes, students feel included. Gireeja started by discussing how study groups could enhance students’ learning experience in large classes. However, finding the right study groups is a challenge. Gireeja discussed some of the difficulties students faced when finding a study group.

Gireeja then discussed her and her coauthors’ partitioning algorithm that helps students find high-quality study groups. She considered student schedules, eagerness to learn the course, and demography when assigning students to groups.

Gireeja surveyed 1000+ students to understand what students wanted from study groups. She discussed the findings from her study, including why students leave study groups. Once the algorithm was applied to the sample, she shared some of her observations regarding the student’s performance.

Wrapping up, she discussed the future direction of the project. Learn more about Gireeja on her website.

Gireeja Ranade

Gireeja Ranade is an Assistant Teaching Professor in Electrical Engineering and Computer Sciences at UC Berkeley. Before joining the faculty at UC Berkeley, she was a Researcher at Microsoft Research AI, Redmond. She has received the NSF CAREER award as well as multiple awards for her teaching. At Berkeley, designed a new introductory course sequence to introduce first-year students to linear algebra, circuit design and machine learning. She regularly teaches courses with 1000+ students and has worked on innovations to teach effectively at this scale.