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Analyzing Human-Computer Interaction as Distributed Cognition: the resources model

Lookup NU author(s): Emeritus Professor Pete Wright, James Fields, Professor Michael HarrisonORCiD

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Abstract

In this article we present a new approach to interaction modeling based on the concept of information resources. The approach is inspired by recent distributed cognition (DC) literature but develops a model that applies specifically to human-computer interaction (HCI) modeling. Of course, there are many approaches to modeling HCI, and the motivation of this article is not to offer yet another approach. Rather, our motivation is that the recent developments in DC are so obviously relevant to HCI modeling and design, yet the ideas have lacked visibility in the HCI community. By providing a model whose concepts are rooted in DC concepts, we hope to achieve this visibility. DC research identifies resources for action as central to the interaction between people and technologies, but it stops short of providing a definition of such resources at a level that could be used to analyze interaction. The resources model described in this article defines a limited number of resource types as abstract information structures that can be used to analyze interaction. We demonstrate how these abstract types can be represented differently in an interface. The resources model uses the concept of interaction strategy to describe the way in which different configurations of resources can differently shape users' actions. These 2 components of the resources model (information structures and interaction strategies), through the process of coordination and integration, provide a link among devices, representations, and actions that is not well articulated in the DC literature.


Publication metadata

Author(s): Wright PC, Fields RE, Harrison MD

Publication type: Article

Publication status: Published

Journal: Human-Computer Interaction

Year: 2000

Volume: 15

Issue: 1

Pages: 1-41

Print publication date: 01/01/2000

ISSN (print): 1044-7318

ISSN (electronic): 1532-7590

Publisher: Lawrence Erlbaum Associates

URL: http://dx.doi.org/10.1207/S15327051HCI1501_01

DOI: 10.1207/S15327051HCI1501_01


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