Investigating the Impact of Language Experience on Second Language Reading Comprehension Using a Resting-State Connectome-based Predictive Model
Restricted (Penn State Only)
Author:
Yu, Anya
Graduate Program:
Psychology
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
June 27, 2022
Committee Members:
Roger Beaty, Major Field Member Frank Hillary, Major Field Member Janet van Hell, Chair & Dissertation Advisor Peggy Van Meter, Outside Unit & Field Member Kristin Buss (she/her), Program Head/Chair
Reading comprehension is an important factor that strongly predicts academic and career success, as well as quality of life indices. As more than half the world now bilingual, second language (L2) reading becomes increasingly more important for educators and psycholinguists to investigate on a theoretical and pedagogical level. Amongst the many factors that are known to affect L2 reading, L2 environment, specifically L2 immersion experience, is anecdotally and empirically impactful towards L2 reading comprehension attainment. However, there are many gaps and issues with how immersion is investigated in the literature. In this dissertation, the first study aims to address the issues of confounding variables, sample size, and standardization of immersion measures that exists in the current literature. The results validated that language diversity entropy is a good standardized qualitative measure of immersion on top of immersion time ratio score, and findings invite future investigations of immersion to employ measures as such to characterize immersion language experience. The second study employs resting-state fMRI to investigate the relationship between immersion language experience, reading comprehension, and intrinsic neural connectivity patterns in the brain using machine learning as an exploratory dive into reading in the brain. Results show that the limbic and cerebellar networks are critically involved in characterizing L2 reading and immersion experience in the brain, which draws important links between immersion and the implicit learning literature. Future studies on immersion should take implicit learning, specifically procedural learning and statistical learning, into account.
