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ABSTRACT
Recently, conventional main control rooms are being gradually replaced by digital main control rooms in nuclear power plants, which results in changes of factors that have effects on diagnosis task performance. The experiment was conducted under four interfaces with different information acquisition methods (Query, Filter, Query-Filter combined, and Visual Search) to explore the influence of cognitive style on diagnosis task performance and possible interaction effects with information acquisition methods. Cognitive style was measured by Index of Learning Styles Questionnaire from four dimensions (Reflective/Active, Intuitive/Sensing, Verbal/Visual, and Global/Sequential). The results showed that cognitive style significantly affected diagnosis task performance, and had interaction effects with information acquisition method. Reflective/Active dimension had significant effect on diagnosis performance under Filter and Query-Filter combined interfaces (active participants performed better). Intuitive/Sensing dimension had significant effect on diagnosis performance under Query and Filter interfaces (intuitive participants performed better). Verbal/Visual dimension had significant effect on diagnosis performance under conventional Visual Search interface (visual participants performed better) and Query interface (verbal participants performed better). The results could be useful for human-machine interface design and the selection of operators in complex industrial systems.
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Notes on contributors
Dan Pan
Dan Pan is a lecturer at the Department of Logistics Engineering, School of Mechanical Engineering, University of Science and Technology Beijing. She received her PhD degree in Management Science and Engineering from Tsinghua University in 2016. Her current research areas include individual characteristics, teleoperation, human-robot interaction, ergonomic design and evaluation.
Lu Yang
Lu Yang received the BS Degree in Industrial Engineering from Tsinghua University in 2016. She completed her undergraduate thesis under the guidance of Zhizhong Li.
Manrong She
Manrong She is a PhD candidate at the Department of Industrial Engineering, Tsinghua University, within the Institutes of Human Factors and Ergonomics. She holds a BS in Industrial Engineering from Tsinghua University.
Xuansheng Ding
Xuansheng Ding is now a researcher in SINOPEC. Her major study field now is the energy industry. She received the master degree in Industrial Engineering from Tsinghua University in 2016.
Zhizhong Li
Zhizhong Li is a full professor at the Department of Industrial Engineering, Tsinghua University. He received his PhD degree in Manufacturing Engineering and Automation from Tsinghua University in 1999. His current research areas include interface design, human error, system safety, and other ergonomics issues associated with complex industrial systems.