Louisa Rosenheck

Analyzing gameplay data to inform feedback loops in The Radix Endeavor

The purpose of this study is to explore some of the ways in which gameplay data can be analyzed to yield results that feed back into the learning ecosystem. There is a solid research base showing the positive impact that games can have on learning, and useful methods in educational data mining. However, there is still much to be explored in terms of what the results of gameplay data analysis can tell stakeholders and how those results can be used to improve learning. As one step toward addressing this, researchers in this study collected back-end data from high school students as they played an MMOG called The Radix Endeavor. Data from a specific genetics quest in the game were analyzed by using data mining techniques including the classification tree method. These techniques were used to examine the relationship between tool use and quest completion, how use of certain tools may influence content-related game choices, and the multiple pathways available to players in the game. The study identified that in this quest use of the trait examiner tool was most likely to lead to success, though a greater number of trait decoder tool uses could also lead to success, perhaps because in those cases players solving problems about genetic traits at an earlier point. These results also demonstrate the multiple strategies available to Radix players that provide different pathways to quest completion. Given these methods of analysis and quest-specific results, the study applies the findings to suggest ways to validate and refine the game design, and to provide useful feedback to students and teachers. The study suggests ways that analysis of gameplay data can be part of a feedback loop to improve a digital learning experience. Situated gaming-learning interactions in The Radix Endeavor were examined.Data mining techniques, including the classification tree method, were employed.Different play patterns for users who eventually or never succeeded were revealed.The trait examiner was a key tool in the quest completion process.Usage patterns can provide meaningful data to designers, teachers, and students.

Tipping the Scales: Classroom Feasibility of the Radix Endeavor Game

The Radix Endeavor is an inquiry-based educational game designed to encourage exploration and experimentation. Its design deeply integrates STEM practices as core game mechanics, enabling students to learn by doing in authentic contexts that are distributed across people, places, and time. Radix is a large-scale game that is not primarily designed to directly teach students math and science facts, but rather to serve as a foundational experience that teachers can integrate into their teaching in personalized and meaningful ways. Teachers have a difficult choice each time they consider implementing a unit of game-based curriculum. They must weigh the educational and pedagogical benefits on the one hand, and the barriers to implementation on the other, in order to decide whether the game is worth implementing in their classroom. In this chapter we discuss the feasibility of implementing the game in the classroom, teacher perceptions of student learning with the game, and the interaction between these two factors.

Designing games for learning and assessment: the radix endeavor

In this paper, we briefly present a design framework, XCD, that we developed through the design of The Radix Endeavor, a multiplayer online game for STEM learning. The framework provides a method for ensuring that the learning objectives, game mechanics, and data collected are closely aligned throughout the design process. We present this method here as a resource for other learning game designers, with the goal of making designing games with deep learning more accessible.