A Systematic Review of Data Collection and Analysis Methods in K–12 Educational Games

• In Event: Sunday Roundtable 9:45 am
  In Roundtable Session: Looking Back to Move Forward: Reviews on Advanced Technologies for Learning (Table 5)

iPresentation URL: https://aera24-aera.ipostersessions.com/Default.aspx?s=B9-E6-F4-78-7E-92-1B-FC-DC-AA-09-7E-68-AA-36-33

Abstract

This paper reports on systematic literature review that examined learning theories and data collection and analysis methods used to study game-based learning in research on educational digital games for K-12 populations. Through electronic database, hand, and ancestral searches, we identified 25 empirical studies (29 educational games) published in peer-review journals that report evidence of how students learn through in-game and out-of-game data collection and analysis methods. Taking an approach to game-based learning as identity-driven and situated, we found that while games do not take such an approach to game-based learning, games tend to collect data on players’ social interactions and collaborative experiences. The review also highlighted the opportunity for providing real-time feedback and data to players during gameplay.

Authors

• Tianyu Ma, University of Miami

• Jennifer Beth Kahn, University of Miami

• Lisa Aileen Hardy, The Concord Consortium

• Sarah C. Radke, Concord Consortium