Analytics-driven design: Impact and implications of team member psychological perspectives on a serious games (SGs) design framework

Abstract

The number of educational or serious games (SGs) available to educators has increased in recent years as the cost of game development has been reduced. A benefit of SGs is that they employ not only lesson content but also knowledge contexts where learners can connect information to its context of use with active participation and engagement. This, in turn, improves learners’ ability to recall, integrate, and apply what they learn. Much of the research on game analytics has examined learner in-game trails to build predictive models that identify negative learner actions (e.g., systematic guessing after the fact). However, analytics can also be used in the game design and development phases. Drawing on evidence-centered design (ECD), the chapter outlines ways that analytics can drive the development of scenarios and activities in a game and thus allows SGs to function as contextual apprenticeships, providing robust assessment opportunities. We describe how ECD theory was applied in a project to develop and test a SG that trains people to reduce their reliance on cognitive biases. We describe instances during the design process where our team encountered obstacles due to differing psychological and learning/teaching orientations, a topic rarely explored in the SG or ECD literature. Furthermore, we describe the final analytics-based game design features. We propose an additional element (persona) and how we anticipate incorporating that ECD extension into future projects.