The metacognitive role of familiarity in artificial grammar learning: transitions from unconscious to conscious knowledge.

We present two methods by which people could learn (e.g., artificial grammars): learning by a single updating model that has the function to reflect how reality is (e.g., the standard types of connectionist models in the implicit learning literature), and learning by the use of considering hypotheticals (hypothesis testing). The first method results in unconscious knowledge of the structure of a domain. Such unconscious structural knowledge can lead to conscious knowledge that new items do (or do not) have that structure (“judgment knowledge”). When unconscious structural knowledge produces conscious judgment knowledge, the phenomenology is of intuition, a common phenomenology in implicit learning experiments. We propose a mechanism by which one becomes aware of judgment knowledge, turning feelings of guessing into those of intuition: feedback in calibrating the accuracy of one’s knowledge of the distribution of familiarity of the test strings. Accurate predictions lead to awareness of knowing, that is, to conscious knowledge. Contrary to some popular beliefs, we argue fluency plays little role in either the expression of unconscious structural knowledge or in the formation of conscious judgment knowledge. The individual difference variable Faith in Intuition was not associated with better implicit learning but it was associated with sensitivity to familiarity and the metacognitive processes by which judgment knowledge can be made conscious: that is, by which feelings of intuition are formed