Enhancing User Understanding in a Decision Support System: A Theoretical Basis and Framework.

Author List: Steiger, David M.;
Journal of Management Information Systems, 1998, Volume 15, Issue 2, Page 199-220.
The primary purpose of decision support systems (DSS) is to help the decision maker develop an understanding of the ill-structured, complex environment represented by the model. This paper concentrates on understanding the modeled environment through model analysis. Specifically, the purpose of this paper is to propose a framework for model analysis based on Perkins's theory of understanding and its basic premise (knowledge as design) and basic components (purpose, models, and arguments). This framework encourages enhanced user understanding in a DSS via the synergistic combination and integration of: (1) cognitive science (theory of understanding), (2) artificial intelligence (machine learning, knowledge extraction, and expert systems), (3) model analysis (deductive and inductive), and (4) DSS (model management, instance management, and knowledge-base management).
Keywords: artificial intelligence; decision support systems; design theory; model management systems; post-optimality analysis; sensitivity analysis; theory of understanding
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#191 0.371 model models process analysis paper management support used environment decision provides based develop use using help literature mathematical presented formulation
#113 0.153 support decision dss systems guidance process making environments decisional users features capabilities provide decision-making user paper findings systems.decision components computer-based
#129 0.147 expert systems knowledge knowledge-based human intelligent experts paper problem acquisition base used expertise intelligence domain inductive rules machine artificial task
#116 0.088 research study influence effects literature theoretical use understanding theory using impact behavior insights examine influences mechanisms specifically context perspective findings
#110 0.086 theory theories theoretical paper new understanding work practical explain empirical contribution phenomenon literature second implications different building based insights need
#207 0.055 design artifacts alternative method artifact generation approaches alternatives tool science generate set promising requirements evaluation problem designed incentives components addressing