Doctoral Dissertation Research: Investigating the role of distribution in syntactic comprehension

People encounter a variety of syntactic structures in everyday language use, whether through reading or spoken conversation. In some cases, sentences can be ambiguous and have more than one meaning. For example, in "The spy saw the man with the binoculars", one interpretation is that the spy is looking through the binoculars, while an alternative interpretation is that the man has the binoculars.

Yet, despite this ambiguity, people are still able to converge on a single interpretation. The mechanisms behind this are still debated today as many factors have been shown to guide comprehension. This dissertation project will investigate how experience with an unfamiliar structure affects language processing.

Experience is thought to play a large role in comprehension, however, despite its large role in theoretical models, there is still no direct evidence of whether people actually keep track of distribution i.e., the relative frequency of a target structure and competing structures.

This doctoral dissertation project investigates whether people can implicitly acquire syntactic distributional information by directly manipulating the relative frequency of syntactic structures while holding overall exposure constant: the probability of an unfamiliar, dialectal structure ("The meal needs cooked", a variation of "The meal needs to be cooked") relative to another competing structure ("The meal needs cooked vegetables"). The dialectal structure is mainly associated with a dialect from Western Pennsylvania, and is unfamiliar to most people outside of this region.

In a series of experiments, self-paced reading is used to test whether a higher proportion of the dialectal structure leads to less processing difficulty over time. The investigators also test whether the distributional information from the verb "needs" can be generalized to a related verb (i.e. "wants"). This project will inform theories of language learning as it provides a stronger test of distributional learning compared to previous studies.

It also seeks to have practical implications for optimum learning strategies for grammar and reading comprehension.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.