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The Absence of Degree of Automation Trade-Offs in Complex Work Settings
Greg A Jamieson1, Gyrd Skraaning2
1213607 University of Toronto, Ontario, Canada.
Human Factors
|July 27, 2019
Summary
This study tested the lumberjack model in a nuclear power plant simulator. Findings indicate the degree of automation (DOA) model contradicts lumberjack predictions in complex scenarios.
Area of Science:
- Human-Computer Interaction
- Automation and Control Systems
- Cognitive Psychology
Background:
- A meta-study suggested degree of automation (DOA) predicts performance, workload, and situation awareness.
- Empirical support for DOA predictions is limited in complex work environments.
Purpose of the Study:
- To evaluate the routine-failure trade-off (lumberjack) model's predictions.
- To test the model in a full-scope simulator with expert operators performing realistic control tasks.
Main Methods:
- Conducted a full-scope nuclear power plant simulator experiment.
- Licensed operating crews performed realistic procedure execution tasks.
- Collected and analyzed dependent measures aligned with the lumberjack model.
Main Results:
- Situation awareness increased with higher degree of automation, contradicting the lumberjack model.
- No significant effects were observed for anticipated workload or failure task performance.
- Results challenge the lumberjack model's applicability in complex work situations.
Conclusions:
- The lumberjack model's predictions may not generalize from simple to complex work situations.
- Further research is needed to validate the lumberjack model in complex operational environments.
- Practitioners should exercise caution when applying lumberjack model predictions to complex scenarios.
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