For the past half-century, psycholinguistic research has concerned itself with two mysteries of human cognition: (1) that children universally acquire a highly abstract, computationally complex set of linguistic rules rapidly and effortlessly, and (2) that second language acquisition (SLA) among adults is, conversely, slow, laborious, highly variable, and virtually never results in native fluency. We now have a decent, if approximate, understanding of the biological foundations of first language acquisition, thanks in large part to Lenneberg's (1964Lenneberg's ( , 1984 seminal work on the critical period hypothesis. More recently, the elements of a promising theory of language and evolution have emerged as well (see e.g. Bickerton, 1981Bickerton, , 1990 Leiberman, 1984 Leiberman, , 1987. I argue here that the empirical foundations of an evolutionary theory of language are now solid enough to support an account of bilingualism and adult SLA as well. Specifically, I will show that evidence from the environment of evolutionary adaptation of paleolithic humans suggests that for our nomadic ancestors, the ability to master a language early in life was an eminently useful adaptation. However, the ability to acquire another language in adulthood was not, and consequently was not selected for propagation.
This paper is a description of a computer based intelligent tutoring system for French as a second language, and of its ancillary grammar editor, which is built on an object oriented, unification-based natural language processor. First I review some of the considerations that motivate using intelligent tutoring systems in second language education. Second, I discuss the details of object oriented programming and unification grammar. Third, I give some examples of how this software interacts with students and of what sort of grammatical phenomena it is capable of handling. I will show how the parser straightforwardly handles some thorny problems of complex grammatical structures (e.g. conjunctions; reflexive binding; phrase embedding; dislocated, missing, or superfluous parts of speech) which have had an inhibitory effect on CALL parsing applications in the past.
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