Abstract

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory–picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test–retest reliability (r = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process.

Highlights

  • Subject Category: Psychology and cognitive neuroscience Subject Areas: psychology Keywords: statistical learning, verbal working memory, incidental learning, online learning, non-adjacent dependencies, probabilistic dependencies

  • The t-values for these confirm that the adjacent deterministic and adjacent probabilistic types were learned significantly compared to the reference type, whereas the non-adjacent deterministic condition did not differ from the random condition

  • We predicted that a grammaticality effect would be seen, and within the grammatical conditions, adjacent deterministic would be the easiest to learn followed by adjacent probabilistic and non-adjacent deterministic conditions

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Summary

Introduction

Subject Category: Psychology and cognitive neuroscience Subject Areas: psychology Keywords: statistical learning, verbal working memory, incidental learning, online learning, non-adjacent dependencies, probabilistic dependencies. We devised an online statistical learning task using real word auditory–picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. Our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Predictability between elements, measured as transitional probability (TP), is the probability of an event b, given that event a has already occurred. It is measured as the number of times that event ab occurs divided by the overall frequency of a.

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