Learning with Data

In the first part of this talk, Dr. Dasgupta will describe some of his work to develop quantitative techniques that help us understand how children learn in informal learning environments online. He will present some of his empirical data scientific studies of Scratch — an online community where tens of millions of young people learn to code in a rich social media context.
In the second part, Dr. Dasgupta will describe his work to put the ability to do this type of learning and social media analytics into the hands of the children who use Scratch. He will focus on Scratch Community Blocks, a system he designed and deployed that lets children in the Scratch community programmatically analyze and visualize their own learning and social activity data. In addition to describing the design work behind the system, he will highlight how children using it (i) analyzed data and created visualizations in ways that connected with their interests, experiences, and aesthetic sensibilities, (ii)  self-reflected upon their own learning and social participation in Scratch, and finally (iii)  engaged in critiques that mirror some of the current critical scholarly debates around data science, reflecting on issues such as privacy and algorithmic bias.

About Sayamindu Dasgupta
Sayamindu Dasgupta is a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington. His research is situated at the intersection of data science, design, and the learning sciences where he uses data scientific methods to understand how children learn in large-scale informal online communities. Additionally, he also designs, deploys, and studies the uses of programming toolkits that enable children to engage in data science. His work has received recognitions and awards in the 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.