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Research
Ellen Bassís research develops theories of human performance, quantitative modeling methodologies, and associated experimental designs that can be used to evaluate human-automation interaction in the context of total system performance. The outcomes of the research can be used in the systems engineering process: to inform system requirements, procedures, display designs and training interventions and to support system evaluation. The long term goal is to develop comprehensive measures, modeling techniques and evaluation methods that capture the contribution of human operators (knowledge, skills, and limitations), the dynamic task environment, the tools used (algorithms, decision support tools, displays), organizational factors (such as team roles) and all of their interactions. Her research contributions can be decomposed into four synergistic areas:

  • Characterizing human judgment and decision making
  • Modeling human judgment when supported by information automation
  • Computational models of human-human and human-automation coordination
  • Design and evaluation of socio-technical system interventions to improve human judgment and decision making