This panel will present Cognitive Work Analysis as a framework that guides the design of information systems. Cognitive Work Analysis embraces complexity by providing for multi-dimensional analyses of the use of information systems and their contexts.
The panel will give an overview of the Cognitive Work Analysis framework including discussions of its historical, methodological, and theoretical position in relation to other movements in Information Science, particular with respect to Human Information Behavior research. Furthermore, the panel will give two examples of how Cognitive Work Analysis can enrich Information Science; one example will discuss the formulation of a work centered approach to the design of classification schemes, and the second example will discuss the analysis of information needs for indexing documents.
The Cognitive Work Analysis framework can be applied to analyze the work people do, the tasks they perform, the decisions they make, their information behavior, and the context in which they perform their work - all for the purpose of systems design. The framework is one of the few tools, which offer a mechanism to transfer results from an in-depth analysis of human-information-work interaction directly to design requirements. Cognitive Work Analysis is useful for the study of human-information interaction and for the design of information systems because: - It provides for a holistic approach that makes it possible to account for several dimensions simultaneously. - It facilitates an in-depth examination of the various dimensions of a context. - It provides a structure for the analysis of human-information interaction, rather than subscribing to specific theories, models, or methods.
The Cognitive Work Analysis framework is a powerful guide for the design of information systems for specific situations because many aspects--personal, social, technological, and organizational--play a role simultaneously and interdependently and the framework provides a means for capturing these and translating them into systems design.