Using Concept Mapping to Define Problems and Identify Key Kernels during the Development of a Decision Support System

Abstract

How does a decision support system (DSS) designer identify the kernel(s) or key decision elements of a problem, from the user's perspective, and develop a design for a DSS from them? The problem arises because DSS adaptive design says start small and grow, but there are no suggestions on where to start. This thesis addresses the primary challenge by developing the tool, concept mapping, as a means to identify kernels in a decision process. This is a descriptive process that defines the problem space, describes the decision process, and identifies the key steps of the decision process as potential kernels. Beyond this initial challenge is the challenge of integrating concept mapping into the adaptive design process. This thesis effort will take the technique of concept mapping and use it to extract the information about a problem from the decision maker himself. The result of this extraction should be a well defined problem space, a sufficiently described decision process and a means to identify the kernels. Finally, the effort turns to integrating concept mapping into the adaptive design process. The integration of concept mapping into the adaptive design process is accomplished through a process called the problem definition process (PDP).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1987
Accession Number
ADA185636

Entities

People

  • Michael R. Mcfarren

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Command And Control
  • Computers
  • Databases
  • Decision Support Systems
  • Doctrine
  • Information Processing
  • Information Systems
  • Instructors
  • Judgment
  • Operations Research
  • Plastic Explosives
  • Prototypes
  • Psychology
  • Students
  • Thinking

Fields of Study

  • Computer science

Readers

  • Statistical inference.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • Space