Beyond Intelligent Interfaces: Exploring, Analyzing and creating Success Models of Cooperative Problem Solving

Abstract

Cooperative problem-solving systems are computer-based systems that augment a person's ability to create, reflect, design, decide, and reason. This work is focused on supporting cooperative problem-solving in the context of high functionality computer systems. Based on the limitations of earlier prototype systems, the authors conducted an empirical study of a success model of cooperative problem-solving between humans in a large hardware store. Insights gained are currently used in the design of integrated, domain-oriented, knowledge-based design environments that serve as a new generation of cooperative problem-solving systems. The authors' goal is to establish the conceptual foundations necessary to use the computational power now becoming available to create cooperative problem-solving systems. They explore conceptual frameworks, methodologies, and technologies to exploit the unique opportunity offered by powerful computer systems. The purpose is to augment human potential and productivity. They characterize some of their older system-building efforts, which addressed isolated aspects of cooperative problem-solving. Next, they briefly describe their application domain -- high functionality computer systems. The core of the paper discusses an empirical study analyzing a success model of cooperative problem-solving among humans as it takes places between customers and sales agents in a large hardware store. They conclude by describing the lessons learned from this study and their impact on future work.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1991
Accession Number
ADA445952

Entities

People

  • Brent Reeves
  • Gerhard Fischer

Organizations

  • University of Colorado Boulder

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Availability
  • Classification
  • Colorado
  • Computers
  • Contracts
  • Demographic Cohorts
  • Environment
  • Information Operations
  • Instructions
  • Laboratory Procedures
  • Lessons Learned
  • Models
  • Monitoring
  • Organizational Structure
  • Prototypes
  • Standards

Fields of Study

  • Computer science

Readers

  • Computer Science.
  • Software Engineering.
  • Systems Analysis and Design