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Predicting Quitting in Students Playing a Learning Game
2018
Educational Data Mining
Identifying struggling students in real-time provides a virtual learning environment with an opportunity to intervene meaningfully with supports aimed at improving student learning and engagement. In this paper, we present a detailed analysis of quit prediction modeling in students playing a learning game called Physics Playground. From the interaction log data of the game, we engineered a comprehensive set of aggregated features of varying levels of granularity and trained individualized
dblp:conf/edm/KarumbaiahBS18
fatcat:vncptisb6nfgldpz7mkbxstbee