Modeling and analysis of a dynamic judgment task using a Lens Model approach

Ann M. Bisantz, Alex Kirlik, Paul Gay, Donita A. Phipps, Neff Walker, Arthur D. Fisk

Research output: Contribution to journalArticlepeer-review


In this research, we investigated performance in a complex, dynamic decision-making task. Individual judgment performance in a command and control environment was modeled as linear combinations of environmental cue values using a Lens Model approach. Examination of the judgment models indicated that participants had similar judgment policies, while correlational and error analyzes indicated that performance differences were due to participants' abilities to execute judgment strategies rather than their knowledge of the task environment. This research demonstrated how the Lens Model approach can be extended to account for dynamic aspects of decision making in complex environments, through the use of individual, time dependent environmental models for each participant. Additionally, the research showed that a Lens Model approach is useful for characterizing factors in individual performance in complex judgment tasks. Empirically, this research suggests that training on task knowledge should be supplemented by training which focuses on the consistent execution of judgment strategies.

Original languageEnglish (US)
Pages (from-to)605-616
Number of pages12
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
Issue number6
StatePublished - Nov 2000
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications


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