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MOGUL framework


The MOGUL framework is a research framework aiming to provide a theoretical perspective on the nature of language. MOGUL (Modular On-line Growth and Use of Language) draws on the common ground underlying various related areas of cognitive science including psycholinguistics, theoretical linguistics, first- and second-language acquisition, neurolinguistics and cognitive psychology; it is designed to be applicable to all these fields of research.

The MOGUL framework's background assumption is that the mind is composed of expert systems which have evolved over time, one of which is responsible for human linguistic ability. Historically, scientific studies of language have been divided between many sub-disciplines; theoretical linguists focus on the abstract properties of language and researchers in other fields investigate how language is used and processed in real time: either in psychological terms or (in the case of neurolinguistics) through a study of the physical systems of neurons in the brain. Each field of study has developed its own research traditions and technical vocabulary, making it difficult to integrate insights across disciplines. The MOGUL Framework represents an attempt to identify common themes and compatible approaches in different (but related fields), and hence to facilitate integration.

MOGUL is designed as a platform for the generation of new hypotheses, with a terminology and a set of interrelated concepts that can be used across more than one discipline. Although not a full-fledged theory in its own right, it sets out various theoretical claims based on the current literature in a range of research domains. As suggested below it is not connectionist in the most widely used sense of that term, although it employs terms and concepts familiar to connectionists such as competition, activation, activation levels and so forth. The same processing perspective also requires the long-established Chomskyan distinction between competence and performance to be viewed in a somewhat different way. Linguistic competence (knowledge) is not compartmentalised and placed in a separate box in the model, which then forms the object for a processor (or processors) to act on. Rather, it is instantiated and implicit within the processing system. The distinction between mental representation and processing is still valid, but is expressed in a way that ought to allow the abstract properties of linguistic systems in the mind to be more easily investigated in conjunction with real-time linguistic phenomena. The inspiration for this approach is the work of Ray Jackendoff. Here the architecture of the language faculty is formulated in such a way as to facilitate statements about competence-related, representational issues and their relationship to real-time language processing within the same model.


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