Academic journal article Human Factors

Contending with Complexity: Developing and Using a Scaled World in Applied Cognitive Research

Academic journal article Human Factors

Contending with Complexity: Developing and Using a Scaled World in Applied Cognitive Research

Article excerpt

Scaled worlds preserve certain functional relationships of a complex task environment while paring away others. The functional relationships preserved are defined by the questions of interest to the researcher. Different scaled worlds of the same task may preserve and pare away different functional relationships. In this paper we use the example of Ned to discuss the use of scaled worlds in applied cognitive research. Ned is based on a detailed cognitive task analysis of submarine approach officers as they attempt to localize an enemy submarine hiding in deep water. For Ned we attempted to preserve the functional relationships inherent in the approach officer's information environment while paring away other aspects of his task environment. Scaled worlds attempt to maintain the realism inherent in the preserved functional relationship while being tractable for the researcher and engaging to the participant.

INTRODUCTION

Commanders of 21st-century submarines will be given computer workstations that will allow them to directly query and receive data regarding hostile, friendly, and neutral targets. (In submariner parlance, all objects in the ocean other than one's ownship are referred to as targets.) Understanding the information needs of the submarine commander in his role as approach officer (AO) is vital to the design of this workstation and is the goal of Project Nemo. (In the U.S. Navy, all submarine officers and crew are male.) This project has required a multiphase approach that combines the applied tools of human factors practitioners, the microworlds approach used by those who study dynamic decision making, and a theoretical perspective drawn from cognitive science.

Project Nemo is a long-term, ongoing research project. The first phase involved analyzing the nature of the expertise used by AOs in localizing enemy submarines hiding in deep water. Our trials and tribulations in analyzing this novel expertise are documented in Gray and Kirschenbaum (in press). The second phase, documented by this paper, involved using the analyses from the first phase to build and deploy a scaled world. Both papers are in keeping with the themes of this special issue, in that their focus is on research methods, not research conclusions. Those interested in the research conclusions of the first phase are directed to Gray, Kirschenbaum, and Ehret (1997) for a short treatment and to Kirschenbaum, Gray, and Ehret (1997) for a detailed account. Those seeking research conclusions from the scaled-world phase must await future publications.

This introduction concludes with two overviews. The first contains a brief description of the motivations of Project Nemo and the AO's task domain. The second discusses the role of scaled worlds and the dimensions on which they differ from other simulated task environments.

Overview of Project Nemo and Situation Assessment

The AO performs the role of senior decision maker during an encounter with a hostile target. The AO's job in identifying and locating enemy submarines is difficult, interesting, and important. It is difficult because it requires locating an enemy who is hidden in a vast and acoustically uncertain ocean environment. It is interesting to cognitive scientists because the expertise of AOs is similar to but different from other, better-studied types of expertise. Finally, whatever the changing nature of warfare, locating hostile targets in an uncertain ocean environment is an important job that is important to do well.

The U.S. Navy is designing a new attack submarine that, among other innovations, will feature a reduced crew and a command workstation for the AO. The results of our project will help inform the design of the command workstation so that the procedures used by AOs in problem solving are supported and facilitated by the workstation. A prerequisite to building such reasoning-congruent interfaces (Merrill, Reiser, Beekelaar, & Hamid, 1992) is a deep understanding of the cognitive procedures and memory structures used by AOs in their task and how these information processes react and interact with external events. …

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