Approaches to illuminate content-specific gameplay decisions using open-ended game data

Games can be rich environments for learning and elicit evidence of students’ conceptual understanding inquiry processes. Illuminating content-specific gameplay decisions, or methods completing game tasks related to a certain domain, requires context that is open-ended enough students make choices demonstrate their thinking. Doing this also log data Game Learning Analytics (GLA) are granular look at the specific most relevant domain. This paper presents research done on student exploration high school level Mendelian genetics in multiplayer online called The Radix Endeavor. study uses three approaches identify decisions distinguish players utilizing different methods, looking actions tool use, play patterns player types, input patterns. In selected quest, were found yield insights into ways complete genetics, suggesting potential set more generalized guiding questions GLA field could adopted by games designers scientists convey information about games.