The vast computational power enabled by parallel programming has led to major advances in data science, scientific computing, and AI. Yet, teaching parallel programming remains challenging: non-deterministic execution introduces an exponential number of possible execution paths, where a single flawed path can undermine an entire program. Games have shown promise in helping students grasp complex concepts, but prior game-based approaches to teaching parallelism have struggled with two key limitations: a lack of strong semantic grounding in concurrency concepts, and weak transfer from visual gameplay to real-world coding practices.

In this paper, we present Parallel X, a redesigned educational game that directly addresses these limitations. It (1) incorporates classic concurrency theory to support debugging tasks, an increasingly vital skill as AI-generated code becomes more common and error-prone, and (2) introduces transfer learning activities that connect in-game states to C++ code, bridging the gap between conceptual understanding and implementation. A usability study with undergraduate CS majors shows improved usability scores and significantly higher ratings for information accessibility compared to an earlier version of the game.