Learnability is often an overlooked and misunderstood aspect of usability. It may be assumed that good UX design will lead to good learnability, but this is not always the case.
A more learnable system is one that reduces the time it takes to complete tasks as users spend more time with that system. This can be especially important in instances when repeated use of a system and a certain amount of training is expected.
Fortunately learnability is easy to quantify and doing so can reveal far more than traditional usability testing.
This presentation will cover:
How to conduct a learning curve test as developed and used by the presenter.
- The learning curve test is simple, flexible and adaptable. It combines timed performance, established usability measures (the SUS and TLX), simple observation, and interviews to deliver task learnability as well as important feedback. This all clearly indicates where and how to improve the system you are testing.
- It also gives some very nice looking graphs.
Two case studies demonstrating what real results look like, pitfalls, problems and the benefits of testing.
- The first case study is a comparison of different user groups operating an electric wheelchair controller. Real world application had to be replicated in a short time and in a controlled environment.
- The second case study covers the process of refining a setup procedure for GPS software on excavators. It shows the adaptability of the learning curve test as (like many things) nothing goes perfectly to plan.