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Research Centers In addition to the six informal research areas, the institute houses four research centers: the Center for Lifelong Learning and Design (L3D), the Center for Computational Language & Education Research (CLEAR) and the Center for Research on Training (CRT) and The Center for Determinants of Executive Function & Dysfunction (DEFD). In contrast to the interdisciplinary research areas, the research centers are formally acknowledged units within the university administrative structure.
Center for Computational Language & EducAtion Research (CLEAR) Co-Directors: James Martin & Martha Palmer The Center for Computational Language & EducAtion Research (formerly known as the Center for Spoken Language Research [CSLR]) at the University of Colorado, Boulder is part of the Institute of Cognitive Science, directed by Marie Banich. The Center's mission is to create the next generation of conversational systems. One of our main objectives is to bring interactive language systems to research laboratories and classrooms throughout the United States, so that a generation of researchers, educators and students can use and investigate these systems and their component technologies. By engaging a large community of researchers and users, we believe that progress in developing interactive language systems will be accelerated, bringing universal access and improved methods and opportunities for lifelong learning to all people. Another main objective of the center is the formulation of new innovative models for speech production, hearing, and language. Such advances will promote the next generation of speech systems, help focus basic speech research on issues which address robustness in real-world settings in the fields of medicine, industry, military, education, and government. Center for Research on Training (CRT) Director: Alice Healy The primary goal of training research in this new Center is to construct
a theoretical and empirical framework that can account for and make accurate
predictions about the effectiveness of different training methods over
a large range of tasks, including military, industrial, vocational, and
academic tasks. The ability to predict the outcomes of different training
methods on particular tasks will, as a natural by-product, point to ways
to optimize training outcomes. Many of the basic mechanisms of knowledge
and skill acquisition are similar across a variety of perceptual, cognitive,
and motor tasks. However, some specific skills have unique features that
might demand special training techniques. The Center focuses on an analysis
of which findings, mechanisms, and principles broadly generalize across
learning types and task requirements. This evaluation allows us to make
specific predictions about the effectiveness of training and general recommendations
to improve training that would apply to virtually any training program.
The Center also aims to identify the unique features of specific knowledge
and skills, where they exist, and how best to train them. The Center is
working to develop taxonomies for both types of training and types of
tasks that will span the range of training types, from classroom to simulator,
and task types, from simple individual laboratory tasks to complex tasks
involving team cognition. The Center efforts include development of several
working predictive models of training effects, making comparisons to assess
their ability to account for and predict training outcomes. Determinants of Executive Function & Dysfunction (DEFD) DEFD is an NIMH Funded Interdisciplinary Behavioral Science Center. The center is designed to understand executive function at three levels: the computational, the psychological, and the neurobiological and integrate them to provide a unified theoretical perspective. To do so, each of DEFD’s projects investigates a particular aspect of executive function at all three levels. One of the center’s projects focuses on the representations supporting executive control and its development during childhood while another examines the effect of emotion on executive function. Other projects investigate executive function by means of analyzing molecular genetic analyses in concert with computational modeling to begin to specify in more detail how the dopamine (DA) system regulates three separable but correlated executive subcomponents -- prepotent response inhibition, updating working memory, and set shifting. Another project utilizes a fMRI/ERP approach to test how well a temporal cascade model of cognitive control can explain facets of executive function, such as task switching. Lastly, we have a project that explores how PFC representations are shaped by the interaction between experience and the unique biological mechanisms of the PFC and associated brain areas in the basal ganglia and dopaminergic system. Only by integrating and synthesizing ideas and findings across these different levels of analysis will the field arrive at a fully adequate understanding of executive function. |
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