There has been a surge of research investigating individual differences in the learning of statistical structure, tying them to variability in a range of cognitive (dis)abilities. In this talk I will present several studies that have demonstrated that individuals’ statistical learning abilities are wildly different from one another. I will show that one's learning performance is relatively stable over time when measured appropriately and that it can help us to predict real-life cognitive abilities.
Ending on a more theoretical note, I will interrogate the question if there is a general statistical learning capacity that can sort individuals from ‘bad’ to ‘good’ statistical learners? Or, is the inter-individual variability in assimilating statistical environments only meaningful within the different cognitive domains? I would like to discuss with you two alternative accounts regarding statistical learning computations which we proposed in a recent TiCS opinion article (Bogaerts, Siegelman, Christiansen & Frost, 2021).