Prediction has been proposed as a mental operation that facilitates language comprehension. That is, when listening to a sentence, a listener makes predictions about up-coming words (for instance, predicting 'sugar' after hearing 'I drink my coffee with cream and ...'). When people's predictions are correct, words are read faster because the person has anticipated what is coming up. Past experimental research has demonstrated that prediction in a reading task is modulated by reading skill. The interpretation of this finding is that because reading exposes people to different types of sentence structures and to a wider range of vocabulary, individuals with high reading skill have added knowledge that can be used to generate accurate predictions. One aspect that has not been considered in past literature, however, is the role of socioeconomic status (SES). This is an important variable to investigate because individuals from low SES backgrounds are also more likely to have less reading experience. Hence, it is unclear whether it is reading skill per se or socioeconomic status that impacts predictive ability. Clarifying this point is the goal of the present doctoral dissertation research study.
Drawing data from participants in a community where literacy and SES are not directly linked, two experiments will be conducted to determine the role of literacy on predictive processing during spoken language comprehension. In Experiment 1, eye movements to objects displayed on a computer screen will be recorded while participants listen to sentences where the cue to anticipation is grammatical. Experiment 2 will also employ an eye tracking technique, this time to examine how grammatical and semantic cues modulate anticipatory processes. Findings from the proposed experiments will be used to create and to offer literacy workshops for diverse and less-advantaged populations.
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.
|Effective start/end date
|2/15/22 → 7/31/23
- National Science Foundation: $18,825.00