AI Magazine
Getting around the task-artifact cycle: how to make claims and design by scenario
ACM Transactions on Information Systems (TOIS)
The Aware Home: A Living Laboratory for Ubiquitous Computing Research
CoBuild '99 Proceedings of the Second International Workshop on Cooperative Buildings, Integrating Information, Organization, and Architecture
Design Science Research Methods and Patterns: Innovating Information and Communication Technology
Design Science Research Methods and Patterns: Innovating Information and Communication Technology
Design and natural science research on information technology
Decision Support Systems
Design science research and the core of information systems
DESRIST'12 Proceedings of the 7th international conference on Design Science Research in Information Systems: advances in theory and practice
An exploratory survey of design science research amongst South African computing scholars
Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
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Constructivist research - learning through building - is the core of a large stream of design science research in IS. Architecture has always explored through this paradigm; more recently, engineering-related disciplines, education and medicine have adopted it as well. Constructivist methods are chosen in all cases because many systems problems are 'wicked': difficult, multi-faceted and frequently exhibiting aspects that emerge only during attempted solution of the problem. Constructivist methods excel at the investigation of incompletely understood problems where the variables of study are inextricably confounded or theory is sparse. In this paper we present two patterns by which the power of constructivist methods can be directed at extending and generating practice-focused results from prior research for the benefit of the Information Systems discipline. The first pattern generates DSRIS projects based on theoretical findings; the second pattern generates DSRIS projects to clarify and extend poorly understood facets of large real-world artifacts/systems.