Stimulus variation-based training enhances artificial grammar learning

Abstract

The current study was designed to explore whether statistical learning ability is affected by the diversity of the stimulus set used in the training phase. The effect of stimulus diversity was assessed by controlling and manipulating the number of exposures to a given set and the number of unique strings presented to the learner during the training phase. 147 students participated in two studies. In the unvaried stimulus study, 71 participants learned the same basic set of 15 exemplars, once(15 × 1 exposure), twice (15 × 2 exposures = 30 total strings) and 3 times (15 × 3 exposures = 45 total strings). In the varied stimulus study, 75 participants learned 15, 30 and 45, all of which were unique, unrepeated exemplars. All groups were asked to classify test strings for their grammaticality following training. Results of the d’ measures in the unvaried stimulus study indicate similar performance across the groups. Conversely, the results of the varied stimulus study show that the group presented with 45 unique strings performed significantly better than the baseline group (15 strings). Analysis of the differences across the equivalent groups in the two studies (15 × 2 exposures vs. 30 unique strings and 15 × 3 exposures vs. 45 unique strings) indicates differences in performance only between the group who was presented with the same 15 strings three times and the group presented with 45 unrepeated strings. Taken together, our results shed additional light on the central role of stimulus variation in Artificial Grammar Learning.