If kids are missing post-test data because the Flanker was too difficult for them to perform, this is MNAR. You know the reason they do not have post-test data and it is not random... Another way to think about the Missing Completely At Random (MCAR), Missing at Random (MAR) and Missing Not At Random (MNAR) designations is based on what the assumptions underlying each categorization allow you to do with your data. MCAR data means in principle that the missingness is ignorable. Because the missing data is unrelated to something measure and unmeasured, you can basically ignore it with confidence that the missingness will not bias your results. MAR assumes that missingness is associate with observables but not unobserved variables and can therefore be modeled and accounted for with minimal bias through multiple imputation or Full Information Maximum Likelihood estimate tor similar.

The problem here is that the missingness is clearly not random, so the question becomes what caused the missingness? Based on 90/258, it sounds as though the task was developmentally inappropriate (although NIH has normative data on flanker from age 4-sensecence) . A whole host of cognitive factors may influence ability/inability to perform the flanker and unless these are measured, you have to assume the MNAR. You should examine whether baseline variables collected are associated with inability to complete T2 flanker - it sounds like you have done this already. But I'd be cautious about any inference following imputing scores because you seem to already know that they were simply not developmentally ready to complete the task.

It is definitely MNAR because there is a logic to the missingness. Unless I don't understand correctly, the underlying mechanism seems to be related to your research questions. So you could transform the missingness into a value in itself (via a recode procedure), and treat it as valid. This is equivalent to modeling the missingness.