Project Summary / Abstract
Adult language knowledge is organized around different levels of linguistic structure: sound categories,
words, sub-word meaningful units, and grammatical rules for combining words into utterances. While
it is widely acknowledged that learning at each level of linguistic representation depends on learning
at other levels, the precise nature of these interactions, as well as the learning mechanisms, remain
unknown. These interactions may support “virtuous cycles” where children's inferences build upon one
another iteratively; the interactions may also introduce vectors for cascading failures, where delays in
learning at one level of representation have wide-reaching effects on learning. As such, characterizing
how these learning processes interact is a critical step towards understanding early language acquisi-
tion, itself a determining factor in early literacy, and in turn early educational attainment.
The proposed project focuses on the acquisition of the English regular plural, an abstract aspect of
language structure which implicates learning at all of these levels, and to which children exhibit an early
sensitivity. Focusing on a carefully selected test case allows for exhaustive experimental characteriza-
tion (Speci¿c Aim 1) and the development of models that capture the interactions between children's
growing knowledge of sounds, meaning, and the grammar (Speci¿c Aim 2). As such, this research
constitutes a ¿rst step towards a broad-coverage mechanistic model of the interactions between learn-
ing processes in early language acquisition. Early language processing abilities are known to be key
contributors to literacy and educational attainment, with subsequent effects for health and well-being.
By providing an enhanced causal model of children's language early language attainment, this research
will help researchers develop better diagnostics and design improved interventions.
The fellowship training plan presented here focuses on 1) deepening the applicant's knowledge of
psycholinguistic modeling techniques and 2) teaching the applicant to run behavioral experiments with
toddlers. The research will be performed at two site: the trainee will work on computational modeling
at MIT (primary host institution, approximately 2/3 of the Fellowship duration), and conduct behavioral
experiments at Duke (approximately 1/3 of the Fellowship duration). This multi-institution setup will
allow the trainee to work with a mentorship team with the specialized knowledge, equipment, and
facilities needed to achieve the project goals, especially sophisticated modeling techniques for language
learning (Dr. Levy, MIT) and experimental techniques for evaluating the language knowledge of toddlers
(Drs. Bergelson and Tomasello, Duke). This combination of mentors, labs, and institutions is perfectly
suited to provide the training necessary to prepare the applicant for a tenure-track professorship, while
answering critical outstanding research questions.