Using Learning Analytics to Support Educational Game Development: A Data-Driven Design Approach

• In Event: 63.084 - Roundtable Session 22
  In Roundtable Session: 63.084-12 - Roundtable Session: The Many Facets of Video Game Communities, Design, and Discourses

Abstract

Big data in education has fostered emergent fields like educational data mining (Baker & Yacef, 2009) and learning analytics (Siemens & Long, 2011). Simulations and educational videogames are obvious candidates for the application of these analytic methods, affording big data situated in meaningful learning contexts (Gee, 2003; Steinkuehler et al., 2012). In design of these educational games, clickstream analytics for core design, alpha usertesting, and final-stage adaptive play design play a key role in optimizing learner experience. This paper maps learning analytics methods to these learning game development phases. Leveraging these powerful analytic tools of visualization, association mining, and predictive modeling throughout the design process is key to supporting players in a user-adaptive, engaging play experience optimized for learning.

Author

• V. Elizabeth Owen, GlassLab Games