About

Aditya Sharma is a Senior Data Scientist with over 6 years of experience in Learning Analytics and Product Analytics using R and SQL. He has a Bachelor's degree in Information Technology from Nirma University. Growing up, Aditya enjoyed Maths and Science and participated in various olympiads in middle school. During his college years, he came across Data Science, which sparked his curiosity, and he started doing some online courses. Predictive analytics became his interest, and he got an internship at Playpower during his last semester of college. Aditya has worked as a Data Science consultant for one of the biggest publishing companies, helping them understand student and teacher usage behaviors, understanding what improves student outcomes, and sharing insights to improve product designs and make data-driven decisions. He has worked on different types of data across projects over the years like event data, student question responses, skill and standard data, school and district demographic data, web analytics data, educational games data, process data, knowledge structure data, support calls data, order and licensing data, roster data, server load data, psychometric data. Aditya has been part of 4 peer-reviewed research papers and wrote an R package called seqClustR to perform sequence clustering on sequential data. He was also awarded Best Short Paper for ‘"Curriculum Pacing: A New Approach to Discover Instructional Practices in Classrooms" at the 14th International Conference on Intelligent Tutoring Systems. Aditya won 2nd Place in the “NAEP (National Assessment of Educational Progress) Educational Data Mining Competition 2019” and was the Winner of “The 2022 EM:IP Cover Graphic/Data Visualization Competition”. The visualization will feature on the cover of one of the upcoming issues of 'Educational Measurement: Issues and Practice'. Currently, Aditya is working at Playpower as a Senior Data Scientist - Learning / Product Analytics. He has created an automated reporting system to generate PDF reports in R using child markdowns for a cognitive tests product with psychometric data. He has designed and coded multiple data dashboards in R shiny (dashboard tool) and SQL at the platform, product, and district levels for product teams, leadership, and district admins. Aditya has also designed ‘EdOptimize’ an open-source learning analytics platform. Aditya's interest areas in data science and learning analytics include statistical modeling, user behavior analysis, storytelling through visualizations, equity in education, machine