Participant Groups and Superlab Remote

Hello,

Working with an undergraduate honors thesis student and we’re having an issue with selecting from participant groups using an exported Superlab Remote experiment. We’ve created two different participant groups (named Order1 and Order2 in order to randomize the order of blocks across participants). When I run the experiment, I get a warning that says “The participant group that you specified, Main Group, does not exist. Would you like to use the group Order1 instead?” This works – can run all the way through the experiment and it saves the data file to the desktop as “Task Data.txt”.

If I select the option “no” in response to this prompt, I’m given the window in which to enter Session ID, participant name, and select the participant group from a drop-down menu, where I can access both order 1 and order 2. This appears to work – allows me to run all the way through the experiment with the blocks displayed in the selected order – but the data file does not save to the desktop (or anywhere else as far as I can tell).

Would love to know if there’s a way to use the participant groups within superlab remote, rather than generating separate files for each randomization order and counterbalancing the versions sent to participants.

Thanks!
Emily

Hello Emily,

When you select “no” and then you get a dialog where you can enter Session ID, etc., that’s actually a bug, not a feature!

Broader point: on one hand, quite frankly, we missed participant groups when we created SuperLab Remote. On the other hand, SuperLab Remote is meant to run without any further input from the participant, so asking them to specify a group goes counter to that idea.

In fact, we are working on a major revision to SuperLab Remote where our focus is on minimizing the number of steps for a researcher to create and share a Remote package and further minimizing the number of steps for the participants.

We have an idea for an elegant solution on how to handle groups, but it will take some time to implement. Please “pardon our dust”, as they say. We will get it right.

Hisham

This makes sense - thanks for the information!