Agnostic Data Acquisition and Interpretation From Novel Contexts: Educational Data Mining for Online Games (Poster 36)

• In Event: AERA Poster Session Nine
  In Poster Session: Learning With Games and Virtual Reality

Abstract

The pursuit of truth lies in our ability to gather data, leverage data to discern patterns among them, and draw inferences that help our society compile evidence. Today, data are abundant, but also obfuscated, disconnected, disaggregated, and disparate. Data exist across myriad sources, platforms, and modalities. Humans interact in unprecedented ways within these contexts; their actions are captured by countless variables and data. Educational Data Mining (EDM) procedures are well suited to document behavior, discern patterns, and understand learning within these systems. EDM is applied to the eSports game League of Legends to mine thousands of cases with more than one million data points to establish the viability of an EDM approach in non-traditional learning environments that generate large-scale data.

Authors

• Mark Carroll, University of Nevada - Las Vegas
  Presenting Author

• P.G. Schrader, University of Nevada - Las Vegas
  Presenting Author