Games+Learning+Society 10 Conference

Discussant:  Jodi Asbell-Clarke

Learning Analytics for Educational Game Design: Mapping Methods to Development
V. Elizabeth Owen
Big data in education (c.f. U.S.DoE, 2012) has fostered emergent fields like educational data mining (Baker & Yacef, 2009; Romero & Ventura, 2010) and learning analytics (Siemens & Long, 2011). Simulations and educational videogames are obvious candidates for the application of these analytic methods (Gee, 2003; Steinkuehler, Barab, & Squire, 2012), affording big data situated in meaningful learning contexts (Mislevy, 2011; Shute, 2011; Clark et al., 2012). In design of these educational games, telemetry-based analytics for core design, alpha usertesting, and final-stage adaptive play design plays a key role in optimizing learner experience. This paper maps a framework of learning analytics methods to learning game development phases – from core data structures, to bug killing, to customized, automatic scaffolding design. 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.

The Common Core State Standards, the Next Generation Science Standards, and the Potential of Digital Game-Based Learning and Assessment
Eric Tucker
Game-based learning and assessment have emerged as promising areas of innovation that could inform and enhance the provision of personalized learning at scale. This paper presents promising practices in the emerging field of technology-enhanced, game-based educational assessment. We examine recent developments in the field and present interviews and case studies to illuminate potential paths along which game-based assessment might evolve. We aim to increase understanding of how game-based assessment could become an integral component of assessment practices and systems, and we encourage the game and assessment industries and advocates to develop game-based assessment products with the potential to enhance meaningful accountability and to inform teaching and learning. We seek to advance games, learning, and assessment as an emerging field and to suggest that game-based assessment may hold relevance for broader conversations about next generation assessments, particularly those aligned with the Common Core State Standards and the Next Generation Science Standards.

Game Design and Player Metrics for Player Modeling in Adaptive Educational Games
Justin Patterson, Aroutis Foster, Jichen Zhu
As data-driven information technology develops, the potential of adaptive educational games becomes increasingly evident. However, much about how to design and develop adaptive learning games is largely not well-understood. In this paper, we present our approach for designing game mechanics and player metrics toward player modeling, necessary steps toward adaptive educational games. Through our on-going Avian project, we demonstrate how we design gameplay activities to support learners of different player types and design player metrics to capture their behavior patterns for player modeling. We believe that the approach behind our game design can be applied in other adaptive educational games that uses player modeling. We also discuss our future plans to player modeling and the evaluation of our approach.