Field studies have frequently been advocated as a means for understanding cognitive activities in naturalistic settings. However, there are several fundamental obstacles that one has to overcome to conduct a field study. This paper discusses two of these obstacles in the context of studying problem solving in complex environments: defining goals of a field study and justifying methods used in data analysis. Based on our experience from a recently finished field study, we outline a framework for understanding the nature of field studies and suggest a specific approach to data analysis. We argue that the goal of field studies should not be limited to hypothesis testing, and that the process of data analysis in field studies can be viewed as an inductive abstraction process. Our field study is used to illustrate the abstraction approach to data analysis and how the obstacles in field studies were dealt with. Through these discussions, we encourage researchers to engage in more field studies.


Field Study Methodology, Cognitive Engineering, Anesthesiology, and Data Abstraction


The research was supported by an IBM Canada Doctoral Fellowship and NSERC Research G r ant #OGP0004101. The writing was partially supported by ONR Grant #N00014-91-J-1540. The authors are grateful f o r the inputs and suggestions of John Doyle and Kim Vicente.

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