![]() We further show how the game mechanics can be extended or adapted to other game-based projects.Īnd two experiments to understand how well viewers can read data from moving visualizations. We describe the construction of this game and report on student projects over two years. The flexibility of the strategies encourages variability, a range of approaches, and solving wicked design constraints. Student teams play against their classmates with the objective to collect the most (good) robots. By designing the game mechanics around four different data types, the project allows students to create a wide array of interactive visualizations. We created an alternative for our information visualization course: Roboviz, a real-time game for students to play by building a visualization-focused interface. These are important skills, but are often secondary course objectives, and unforeseen problems can majorly hinder students. Unfortunately, many projects suffer from ambiguous goals, over or under-constrained client expectations, and data constraints that have students spending their time on non-visualization problems (e.g., data cleaning). Students take on a client-real or simulated-a dataset, and a vague set of goals to create a complete visualization or visual analytics product. Due to their pedagogical advantages, large final projects in information visualization courses have become standard practice.
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