Training study with training criterion
I am new to OpenSesame and can't seem to figure out how to implement an experiment with a training phase and a test phase, whereby participants have to pass a certain accuracy score in the training phase before moving on to the test phase.
The training phase consists of a maximum of 8 blocks. Each block consists of 48 trials. Training criterion is 85%. If participants never reach criterion (per block, not accumulated across blocks), then they complete 8 training blocks and after that move on to the test phase. However, if at the end of any given block participants reach 85% (or higher) in that block, then they move on to the test phase (without completing the rest of the training blocks). This means that participants will differ in how many training blocks they complete.
I have seen this post on meta loops, and the problem is similar but differs in that I do not want to rerun the same block but either move on to the next training block (which differs from the preceding one) or move on to the test phase (and skip the rest of the training blocks).
Thanks for any advice!