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Discovering the events expert practitioners extract from dynamic data streams: the modified unit marking technique

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Abstract

One of the cornerstones of expert performance in complex domains is the ability to perceive problem situations in terms of their task-relevant semantic properties. One such class of properties consists of phenomena that are defined in terms of patterns of change over time, i.e., events. A basic pre-requisite for working towards tools to support event recognition is a method for understanding the events that expert practitioners find meaningful in a given field of practice. In this article we present the modified unit marking procedure (mUMP), a technique adapted from work on social perception to facilitate identification of the meaningful phenomena which observers attend to in a dynamic data array. The mUMP and associated data analysis techniques are presented with examples from a first of a kind study where they were used to elicit and understand the events practitioners found meaningful in a scenario from an actual complex work domain.

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Notes

  1. Not surprisingly, active segmentation produced some additional activity in the motor and prefrontal regions that was not seen in the passive viewing condition. This was likely a result of decision and execution processes associated with the button pressing task (Zacks, personal communication).

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Acknowledgments

The study of event recognition by experienced practitioners which stimulated and tested the development of this method was sponsored in part by NASA under grant NAG9-1005. Additional support to develop this method for studying event patterns was provided through participation in the Advanced Decision Architectures Collaborative Technology Alliance sponsored by the U.S. Army Research Laboratory under Cooperative Agreement DAAD19-01-2-0009.

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Authors and Affiliations

  1. Cognitive Systems Engineering Laboratory, Institute for Ergonomics, The Ohio State University, Columbus, OH, USA

    Klaus Christoffersen & David D. Woods

  2. Department of Anesthesiology, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA

    George T. Blike

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  1. Klaus Christoffersen
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  2. David D. Woods
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  3. George T. Blike
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Correspondence to David D. Woods.

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Christoffersen, K., Woods, D.D. & Blike, G.T. Discovering the events expert practitioners extract from dynamic data streams: the modified unit marking technique. Cogn Tech Work 9, 81–98 (2007). https://doi.org/10.1007/s10111-006-0043-y

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