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Digital learning environments emphasize learning in action. Because knowledge is present in what learners do, how they do it, what tools they use, and how they communicate in and about their doing, it is important to assess knowledge production in context and learning in action. Via a design-based research approach, we explored the feasibility and validity of using evidence-centered design with Bayesian networks to assess mathematical learning in action in a game-based learning environment. We iteratively tested the assessment models and alternative approaches of exploiting game-based performance data, via longitudinal data sets collected during the course of 42 gaming sessions across 3 academic semesters. The investigation illustrated design and implementation heuristics related to game-based learning-in-action assessment.