This thesis explores the development of a strategy game designed to train critical reading skills while generating high-quality data on media bias. Players take on the role of news outlet owners, making publishing decisions that influence their audience and market position. As players improve in identifying bias, their input becomes valuable for data collection. The core challenge lies in making the labeling process engaging enough to be perceived as a game, creating a mutually beneficial outcome of learning and data generation.