About my research
My post-doc project in Dr. Jonathan Brennan's Computational Neurolinguistics Lab at the University of Michigan involves taking EEG recordings from interlocutors in unscripted conversation to build a neurolinguistic corpus of naturalistic native and second language speech. In a subsequent step, we test competing models of L1 and L2 grammar processing to see which theories better align with the observed brainwaves. This takes inspiration from the excellent book chapter "Using free, unscripted conversation with synchronized neuroimaging data in linguistic inquiry" (Tremblay et al. , 2019. In The description, measurement, and pedagogy of words). For more details see NSF award number 2203723.
My doctoral dissertation at the University of Illinois - Chicago (in Dr. Kara Morgan-Short's Cognition of Second Language Acquisition lab) involved using machine learning analyses to pull apart neural indices of conscious vs. subconscious second language processing. In my experiment, participants were exposed to an artificial language with a hidden grammar pattern. By triangulating language task reaction times, subjective, reports, and EEG data, I investigated whether focusing on a grammar rule can help or hinder acquisition at a more implicit level. The long game is to find an optimal trade-off between form-based vs. meaning-based approaches to learning languages, for example, so that even individual L2 learners can deliberately change the way that they allocate attention during real-time second language processing to improve acquisition in the long run. The cherry on top would be to tailor these recommendations according to individuals' particular profiles (which may vary along dimensions of working memory, executive control, sheer tolerance for boredom during repetitive practice, etc., etc.).
I'm also interested in how grammar learning can be conceived as the gradual acquisition of recurring statistical patterns in the input, such that grammatical constructions emerge gradually as the result of processes of abstraction over individual exemplars of a particular form. Language educators could facilitate this whole process by manipulating factors like token frequency ("How often do you encounter this particular form?"), type frequency ("How many different candidate forms do you usually see in this particular context?"), and input skewedness ("For this kind of context, to what extent does one or a few forms make up the lion's share of the input?"). Beyond informing psycholinguistic theory, this second research interest of mine could provide suggestions for language educators by addressing questions such as: does encountering a form more frequently necessarily make it easier to recognize and produce? Is it better to teach new grammar by using a wide variety of words in the examples, or by sticking to a few familiar vocabulary items? Should teachers approximate the input frequencies encountered “in the real world,” or is it possible to tailor classroom input to facilitate L2 acquisition?
I've also dipped my toes into corpus research with projects like:
- profiling the richness of language learner vocabulary through word frequency analyses of written essays
- analyses of how semantic word properties affect development of Spanish dative constructions across L2 writers at different proficiency levels
- comparisons of heritage vs. native speaker collocations in Spanish dative clitics
Check out some recorded conference presentations below!
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