CSL

Principal Investigator: John D. Lee

General Description

The Cognitive Systems Laboratory (CSL) focuses on cognitive engineering, where the challenge is to understand and improve the capacity of joint human-technology systems. This research has considered technology insertion in the maritime industry, ground transportation, tele-operation, and process control. A specific example is the distraction potential of in-vehicle information systems, such as cellular telephones and e-mail. Another example is the role of trust and appropriate reliance in the supervisory control of automation, such as unmanned aerial vehicles (UAVs). In each of these examples, the ultimate goal is to develop computational models of human performance and design principles that can support effective and humane use of technology.

The common theme of understanding how technology mediates peoples' attention integrates CSL's research across the varied research domains of maritime navigation, process control, and driving. Technology-mediated attention builds upon the basic psychological concepts of attention to understand how technology must be shaped so that people attend to the right thing at the right time and respond appropriately. An understanding of how technology can mediate attention is used to create display and control systems that enable people to work effectively with increasingly sophisticated technology.

Students in the CSL learn how to conduct experiments in microworld and simulator environments. They also learn techniques of computational cognitive engineering to model joint human-technology behavior, estimate the state of the operator, and to enhance data interpretation.

Members

PI: John D. Lee
Mai Lee Chang
Pat Ferrara
Joshua D. Hoffman
Joonbum Lee
Monica N. Lees
Michelle Reyes
Shannon Roberts
Bobbie D. Seppelt
Lora Yekhshatyan

Alumni

Timothy Brown
Matthew Brown
Ji Gao
Sameer Khan
Yi-Ching? Lee
Yulan Liang
Cameron Miller
Tara Smyser
Heather Stoner
Julie Ulland

Key Terms

Automation Reliance
Cognitive Assessment
Cognitive Modeling
Interface Design

References

Most Recent
Gao, J., Lee, J.D., & Zhang, Y. (2006). A dynamic model of interaction between reliance on automation and cooperation in multi-operator multi-automation situations. International Journal of Industrial Ergonomics, 36(5), 511-526.
Hoffman, J.D., Lee, J.D., McGehee, D.V. et al. (2005). Visual sampling of in-vehicle text messages - Effects of number of lines, page presentation, and message control. Transportation Research Record (1937), 22-30.
Lee, J.D., & See, K.A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50-80.
Seppelt, B.D., Lee, J.D. (2007). Making adaptive cruise control (ACC) limits visible. International Journal of Human-Computer Studies.

Frequently Viewed
Lee, J.D., & See, K.A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50-80.
Lee, J.D., McGehee, D.V., Brown, T.L., & Reyes, M.L. (2002). Collision warning timing, driver distraction, and driver response to imminent rear end collisions in a high-fidelity driving simulator. Human Factors, 44(2), 314-334.

Cross References

UIowa CSL home page
How to format page numbers in Word
How to create effective powerpoint presentations

Intra-CSL Links

CSL Simulator Network
IRB Issues
Sockets
Past Posters
Useful General Research Readings