Sayamindu Dasgupta: Learning with Data

Join SILS for a special presentation by Sayamindu Dasgupta, a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington. Dasgupta is set to deliver his talk, ‘Learning with Data,’ on Thursday, Nov. 30, 2017 at 3:30 p.m. in Manning Hall 001.

Abstract: In this talk, I will present my work to engage children in doing data science. This work has proceeded through two broad strands—first, through the design and study of new tools to support data science education for youth, and second, through the use of data science to understand how to best support youth learning. The empirical setting for my talk will be Scratch, an online community where tens of millions of young people learn to code in an informal social context.

In presenting the first strand, in addition to describing the design behind learning systems that I have developed, I will highlight how children using them (i) collected and analyzed data in ways that connected with their interests, experiences, and aesthetic sensibilities, (ii) self-reflected upon their own learning and social participation, and finally, (iii) engaged in critiques that mirror some of the current critical debates around data science, reflecting on issues such as surveillance and algorithmic bias.

In presenting the second strand, I will describe some of my empirical data scientific studies conducted in the context of online informal learning, and show how those studies advance our understanding of factors (e.g. design decisions) that support learning.

Bio: Sayamindu Dasgupta is a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington. In his research, Sayamindu designs and studies the uses of programming toolkits that enable children to engage in data science. Additionally, he also uses data scientific methods to understand how children learn in large-scale informal online communities. His work has received recognition and awards in the ACM CHI, ACM CSCW, ACM IDC, and IEEE VL/HCC conferences, and in 2014, he was named in Forbes magazine’s 30 under 30 list for education. He received his doctorate from MIT, where he was a key member of the team behind the Scratch programming language and online community.