How do you determine the order of tasks in a usability test? Do you for example avoid putting tasks with similar paths one after another?
Put them in the order that's most realistic. It doesn't matter if repeated tasks will become easier due to parallels between them if they'll be repeated in real life. It does matter if a test reveals a piece of info that inflects a later task when the latter will usually be done first.
If there's no obvious order, you might ask your users what sorts of things they'd do after completing the current task, and see if that leads on to any obvious action.
This is my general approach.
First I see if the things I want to test can be turned into a higher level task that touches upon the issues that we want to look at in a way that reflects 'normal' usage patterns. For example we might be interested in looking at whether people:
- Can register
- Can log in
- Can log out
- Can find the latest news page
- Can post a comment on a page
- Can edit their profile.
Might turn into:
Can you post a comment on the latest news page? (requires them to register, find the latest news page, and post a comment.
Can you log out
Can you edit your profile (requires them to login and edit profile).
If groups of tasks are independent I'd likely randomise the order I present them to see if there are any dependency-related issues that pop out.
I'd also worry that if I have a lot of tasks with repetitions that I might be trying to get people to do things that they normally wouldn't do in a session with the system.
If your testing is set up in a way that the recruitment is an expensive task it's tempting to get a few users in for long test with many tasks. If the thing your testing is only normally used for 10m then you're then not testing a realistic scenario. It may be better to figure out ways to do more small tests with few tasks, than few long tests with many tasks.
I would suggest that you put the tasks which are most important or of interest to you first, simply because users might be most engaged and focused at the beginning, and as they get towards the end other factors (e.g. familiarity, fatigue, disinterest, etc.) sets in. But many of these factors can be mitigated by good experimental design to remove these biases.