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Identifying levels of success is useful when there are reasonable shades of gray associated with task success. The user receives some value from completing a task partially. Think of it as partial credit on a homework assignment if you showed your work, even though you got the wrong answer. For example, assume that a user’s task is to find the least expensive digital camera with at least 10 megapixel resolution, at least 12× optical zoom, and weighing no more than 3 pounds. What if the user found a camera that met most of those criteria but had a 10× optical zoom instead of 12×? According to a strict binary success approach, that would be a failure. But you’re losing...


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