One current [research] focus is on the so-called "achievement gap," which refers to the lower achievement of poor and minority children in school, particularly in areas such as reading. We have begun a project that examines factors that affect African American children's early school achievement, funded by a significant seed grant from the Wisconsin Institutes for Discovery. This research is being conducted by Julie Washington and Jan Edwards (Comm Dis), David Kaplan (Ed Psych), Maryellen MacDonald, Jenny Saffran, and myself (Psychology), as well as several other faculty. The focus is on ways in which language background affects early school achievement. Most African American children speak the dialect termed African American English, whereas the language in the school is some version of "standard" (also called "mainstream") American English. This dialect mismatch has many effects on the African American child's school experience; it makes tasks such as learning to read literally more difficult than for children for whom there is no dialect mismatch. Our studies focus on young children's knowledge of the alternative dialects, factors that affect ability to switch between dialects, and ways that negative effects of the mismatch can be ameliorated. The idea is to provide supplementary language experiences early, when the child's plasticity for language is high. We can also use our computational models of reading to predict where dialect differences will interfere with progress, and how experience can be structured to improve performance.Seidenberg's "connectionist" model of language learning and grammar contradicts Chomsky:
Mark S. Seidenberg
Donald O. Hebb Professor
Psychology and Cognitive Neuroscience
Overview of Research
[S]ince Chomsky's early work, knowledge of language has been equated with knowing a grammar. Many consequences followed from this initial assumption. For example, if the child's problem is to converge on the grammar of a language, then the problem does seem intractable unless there are innate constraints on the possible forms of grammar. What if we abandon the assumption that knowledge of language is represented as a grammar in favor of, say, neural networks, a more recently developed way of thinking about knowledge representation, learning, and processing? Do the same conclusions about the innateness of linguistic knowledge follow? The answer is: not at all.publications
Our goal, then, has been to articulate an alternative framework for thinking about the classic questions listed above. This is not easy: traditional grammarians have about a 40 year lead on us, and only a few linguists actually think the alternative approach will succeed. However, it's a very interesting moment in the study of language. For many years the study of language was dominating by theoretical linguistics, particularly syntax. More recently, there have been important insights coming from outside of traditional grammatical theory: from computational modeling, from studies of the brain bases of learning and neurodevelopment, from renewed interest in the statistical properties of language (which were ignored for many years following Chomsky's famous observations about the statistical triviality of sentences such as "Colorless green ideas sleep furiously").
Chomsky and his followers have always had their critics. However, there was never an alternative theory that could explain basic facts, such as how children acquire language under the conditions that they do. I think for the first time we have the major components of such a theory in hand. And they suggest the remarkable possibility that the standard conclusions about the nature of language and how it is acquired are just dead wrong. This would be an incredible turn of events, a major development in the intellectual history of the study of language.
That's why it's an interesting moment to be studying language.