Integrating science and management through collaborative learning and better information management

Achieving more sustainable land and water use depends on high-quality information and its improved use. In other words, better linkages are needed between science and management. Since many stakeholders with different relationships to the natural resources are inevitably involved, we suggest that collaborative learning environments and improved information management are prerequisites for integrating science and management. Case studies that deal with resource management issues are presented that illustrate the creation of collaborative learning environments through systems analyses with communities, and an integration of scientific and experiential knowledge of components of the system. This new knowledge needs to be captured and made accessible through innovative information management systems designed collaboratively with users, in forms which fit the users' 'mental models' of how their systems work. A model for linking science and resource management more effectively is suggested. This model entails systems thinking in a collaborative learning environment, and processes to help convergence of views and value systems, and make scientists and different kinds of managers aware of their interdependence. Adaptive management provides a mechanism for applying and refining scientists' and managers' knowledge. Copyright (C) 2003 John Wiley Sons, Ltd.

A work domain analysis framework for modelling intensive care unit patients

Work domain analysis (WDA) has been applied to a range of complex work domains, but few WDAs have been undertaken in medical contexts. One pioneering effort suggested that clinical abstraction is not based on means-ends relations, whereas another effort downplayed the role of bio-regulatory mechanisms. In this paper it is argued that bio-regulatory mechanisms that govern physiological behaviour must be part of WDA models of patients as the systems at the core of intensive care units. Furthermore it is argued that because the inner functioning of patients is not completely known, clinical abstraction is based on hypothetico-deductive abstract reasoning. This paper presents an alternative modelling framework that conforms to the broader aspirations of WDA. A modified version of the viable systems model is used to represent the patient system as a nested dissipative structure while aspects of the recognition primed decision model are used to represent the information resources available to clinicians in ways that support lsquoif...thenrsquo conceptual relations. These two frameworks come together to form the recursive diagnostic framework, which may provide a more appropriate foundation for information display design in the intensive care unit.

Towards evidence-based guidelines for wise use of computers by children

This paper argues for the systematic development and presentation of evidence-based guidelines for appropriate use of computers by children. The currently available guidelines are characterised and a proposed conceptual model presented. Five principles are presented as a foundation to the guidelines. The paper concludes with a framework for the guidelines, key evidence for and against guidelines, and gaps in the available evidence, with the aim of facilitating further discussion. Relevance to industry The current generation of children in affluent countries will typically have over 10 years of computer experience before they enter the workforce. Consequently, the primary prevention of computer-related health disorders and the development of good productivity skills for the next generation of workers needs to occur during childhood. (c) 2006 Elsevier B.V. All rights reserved.

Cognitive neuroimaging: Cognitive science out of the armchair

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the Study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and Subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuromiaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory. (C) 2005 Elsevier Inc. All rights reserved.