How to measure learnability of a user interface
https://voltomedia.com/fresh/wp-content/uploads/1571748390_Save-20-on-millions-of-thumb-stopping-jaw-dropping-visuals.png What Is Learnability? Learnability is one of the five quality components of usability (the others being efficiency, memorability, errors, and satisfaction). Testing learnability is especially valuable for complex applications and systems that users access frequently, though knowing how quickly users can acclimate to your interface is valuable for even objectively simple systems. Learnability considers how easy it is for users to accomplish a task the first time they encounter the interface and how many repetitions it takes for them to become efficient at that task. In a learnability study, we want to produce a learning curve, which reveals longitudinal changes of a quantified aspect of human behavior. With the data from the learning curve, we can identify how long it takes users to reach saturation — a plateau in our charted data which tells us that users have learned the interface as much as possible. For example, let’s say we are redesigning an enterprise file-backup application intended to be run by IT administrators on a regular basis. We assume users will use the application frequently enough that they will progress up that learning curve. For such an application, it is crucial that users be able to complete their work as fast as possible. In this scenario, a learnability study will determine how fast administrators learn to run a backup efficiently. We recruit several representative users and invite them to the lab. Then we ask them to perform the backup and measure how long they take to do so for the first time. Next, we ask them to come back into the lab and do the task for a second time — again, measuring their task-completion time. This process repeats for several more times. The result of our study will be a learning curve which plots the task time over a set number of trials. This learning curve shows the hypothetical completion time for a backup as a function of the number of task repetitions (or trials). Notice that the time for the first repetition is longest, and then the completion time decreases — by trial 4, it levels off, reaching the saturation plateau. Although details such as how many repetitions are needed to reach saturation will vary from case to case, this learning curve is representative of all human learning. Learnability vs Efficiency There are 3 different aspects of learnability, each of which is important to different kinds of users: First-use learnability: How easy is it to use the design the first time you try? This aspect of learnability is of interest to those users who will only perform the task once. These users won’t progress up the learning curve, so they don’t care how it looks. Steepness of the learning curve: How quickly do people get better with repeated use of the design? This facet of learnability is particularly important for users who will use the design multiple times, even though they won’t use it excessively. If people feel that they are progressing and getting better and better at using your system, they’ll be motivated to stick with it. (And conversely, if people feel that it’s hardly getting better, no matter how hard they try, they’ll start looking for a better solution.) Efficiency of the ultimate plateau: How high is the productivity that users can reach with this interface, once they have fully learned how to use it? This aspect is particularly important for people with a frequent and long-lasting need to use the system — for example, when it’s the main tool for important everyday tasks. Ideally, of course, your system should fare well on all 3…
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