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Second Language Processing and Linguistic Theory  

John Archibald

The distinction between representations and processes is central to most models of the cognitive science of language. Linguistic theory informs the types of representations assumed, and these representations are what are taken to be the targets of second language acquisition. Epistemologically, this is often taken to be knowledge, or knowledge-that. Techniques such as Grammaticality Judgment tasks are paradigmatic as we seek to gain insight into what a learner’s grammar looks like. Learners behave as if certain phonological, morphological, or syntactic strings (which may or may not be target-like) were well-formed. It is the task of the researcher to understand the nature of the knowledge that governs those well-formedness beliefs. Traditional accounts of processing, on the other hand, look to the real-time use of language, either in production or perception, and invoke discussions of skill or knowledge-how. A range of experimental psycholinguistic techniques have been used to assess these skills: self-paced reading, eye-tracking, ERPs, priming, lexical decision, AXB discrimination, and the like. Such online measures can show us how we “do” language when it comes to activities such as production or comprehension. There has long been a connection between linguistic theory and theories of processing as evidenced by the work of Berwick (The Grammatical Basis of Linguistic Performance). The task of the parser is to assign abstract structure to a phonological, morphological, or syntactic string; structure that does not come directly labeled in the acoustic input. Such processing studies as the Garden Path phenomenon have revealed that grammaticality and processability are distinct constructs. In some models, however, the distinction between grammar and processing is less distinct. Phillips says that “parsing is grammar,” while O’Grady builds an emergentist theory with no grammar, only processing. Bayesian models of acquisition, and indeed of knowledge, assume that the grammars we set up are governed by a principle of entropy, which governs other aspects of human behavior; knowledge and skill are combined. Exemplar models view the processing of the input as a storing of all phonetic detail that is in the environment, not storing abstract categories; the categories emerge via a process of comparing exemplars. Linguistic theory helps us to understand the processing of input to acquire new L2 representations, and the access of those representations in real time.

Article

Lexical Representations in Language Processing  

Gary Libben

Words are the backbone of language activity. An average 20-year-old native speaker of English will have a vocabulary of about 42,000 words. These words are connected with one another within the larger network of lexical knowledge that is termed the mental lexicon. The metaphor of a mental lexicon has played a central role in the development of theories of language and mind and has provided an intellectual meeting ground for psychologists, neurolinguists, and psycholinguists. Research on the mental lexicon has shown that lexical knowledge is not static. New words are acquired throughout the life span, creating very large increases in the richness of connectivity within the lexical system and changing the system as a whole. Because most people in the world speak more than one language, the default mental lexicon may be a multilingual one. Such a mental lexicon differs substantially from a lexicon of an individual language and would lead to the creation of new integrated lexical systems due to the pressure on the system to organize and access lexical knowledge in a homogenous manner. The mental lexicon contains both word knowledge and morphological knowledge. There is also evidence that it contains multiword strings such as idioms and lexical bundles. This speaks in support of a nonrestrictive “big tent” view of units of representation within the mental lexicon. Changes in research on lexical representations in language processing have emphasized lexical action and the role of learning. Although the metaphor of words as distinct representations within a lexical store has served to advance knowledge, it is more likely that words are best seen as networks of activity that are formed and affected by experience and learning throughout the life span.

Article

Learning and Using Morphology and Morphosyntax in a Second Language  

Laurie Beth Feldman and Judith F. Kroll

We summarize findings from across a range of methods, including behavioral measures of overall processing speed and accuracy, electrophysiological indices that tap into the early time course of language processing, and neural measures using structural and functional imaging. We argue that traditional claims about rigid constraints on the ability of late bilinguals to exploit the meaning and form of the morphology and morphosyntax in a second language should be revised so as to move away from all or none command of structures motivated from strict dichotomies among linguistic categories of morphology. We describe how the dynamics of morphological processing in neither monolingual or bilingual speakers is easily characterized in terms of the potential to decompose words into their constituent morphemes and that morphosyntactic processing is not easily characterized in terms of categories of structures that are learnable and those that are unlearnable by bilingual and nonnative speakers. Instead, we emphasize the high degree of variability across individuals and plasticity within individuals in their ability to successfully learn and use even subtle aspects of a second language. Further, both of the bilingual’s two languages become active when even one language is engaged, and parallel activation has consequences that shape both languages, thus their influence is not in the unidirectional manner that was traditionally assumed. We briefly discuss the nature of possible constraints and directions for future research.

Article

Connectionism in Linguistic Theory  

Xiaowei Zhao

Connectionism is an important theoretical framework for the study of human cognition and behavior. Also known as Parallel Distributed Processing (PDP) or Artificial Neural Networks (ANN), connectionism advocates that learning, representation, and processing of information in mind are parallel, distributed, and interactive in nature. It argues for the emergence of human cognition as the outcome of large networks of interactive processing units operating simultaneously. Inspired by findings from neural science and artificial intelligence, connectionism is a powerful computational tool, and it has had profound impact on many areas of research, including linguistics. Since the beginning of connectionism, many connectionist models have been developed to account for a wide range of important linguistic phenomena observed in monolingual research, such as speech perception, speech production, semantic representation, and early lexical development in children. Recently, the application of connectionism to bilingual research has also gathered momentum. Connectionist models are often precise in the specification of modeling parameters and flexible in the manipulation of relevant variables in the model to address relevant theoretical questions, therefore they can provide significant advantages in testing mechanisms underlying language processes.