Visualizing Learning in a Social Data Science Educational Game World

Abstract

Our poster explores visualization methods for participation in an identity-aligned, multiplayer video game world for learning data science through relationship and community building. We extend methods of representing engagement and learning in both educational games and in data science education contexts. Using simulated game play data and screen capture records of interviews with middle school girls playing an early version of the game, we explore representations for individual and multiplayer learning.