Revealing Differences in Designers’ and Users’ Perspectives
Monitoring complex systems includes scanning, aggregating and processing data from various sources. The design of graphical interfaces for monitoring tasks involves a fine-grained exploration of the importance and expected frequency of events that an operator needs to be informed about.
The Human Efficiency Evaluator is a tool for the prediction of human behavior. We extended it to predict the distribution of operator’s attention while monitoring interfaces. The prediction is based on the SEEV model. We show that our tool can be used by experts with different backgrounds to generate predictions following a structured, semi-automated process.
In a qualitative study with subject matter experts, we analyzed different HMI designs for a navigation task in the maritime domain. We evaluated their modeling time, tested different prediction result visualizations, and investigated in the model differences between the subjects. Different to what we originally expected, the study revealed that the models created by the subjects substantially differ depending on their perspectives. Heat maps visualizing the predicted attention allocation were appreciated by the subjects and enabled them to argue about their perspective.
KeywordsVisual attention HMI analysis Monitoring task
The HEE is developed in the EU ARTEMIS JU project HoliDes (http://www.holides.eu/) SP-8, GA No.: 332933. Any contents herein reflect only the authors’ views. The ARTEMIS JU is not liable for any use that may be made of the information contained herein.
- 1.International Maritime Organization. Annex 24 – MCA guidance notes for voyage planning. Technical report, IMO RESOLUTION A.893(21) (1999). https://mcanet.mcga.gov.uk/public/c4/solas/solas_v/Annexes/Annex24.htm Accessed 15 April 2015
- 2.Grech, M.R., Horberry, T., Smith, A.: Human error in maritime operations: analyses of accident reports using the leximancer tool. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 46, pp. 1718–1721. SAGE Publications (2002)Google Scholar
- 3.Bowditch, N.: The American Practical Navigator: An Epitome of Navigation. Paradise Cay Publications, Arcata (2002)Google Scholar
- 7.Wortelen, B.: Das Adaptive-Information-Expectancy-Modell zur Aufmerksamkeitssimulation eines kognitiven Fahrermodells. Ph.D. thesis, Universität Oldenburg, Fakultät II Informatik, Wirtschafts- und Rechtswissenschaften, Department für Informatik (2014)Google Scholar
- 8.Wortelen, B., Lüdtke, A.: Adaptive simulation of monitoring behavior. In: The Sixth International Conference on Advances in Computer-Human Interaction (2013)Google Scholar
- 9.Lüdtke, A., Osterloh, J-P., Frische, F.: Multi–criteria evaluation of aircraft cockpit systems by model–based simulation of pilot performance. In: Proceedings of ERTS - Embedded Real Time Software and Systems (2012)Google Scholar
- 10.Wickens, C.D., McCarley, J.S., Alexander, A.L., Thomas, L.C., Ambinder, M., Zheng, S.: Attention-situation awareness A-SA model of pilot error. In: Foyle, D.C., Hooey, B.L. (eds.) Human Performance Modeling in Aviation, pp. 213–239. CRC Press, New York (2008)Google Scholar
- 11.Forsythe, C., Bernard, M.L., Goldsmith, T.E. (eds.): Cognitive Systems: Human Cognitive Models in Systems Design. Psychology Press, New York (2006)Google Scholar
- 12.Wickens, C., Sebok, A., Keller, J., Peters, S., Small, R., Hutchins, S., Algarín, L., Gore, B.F., Hooey, B.L., Foyle, D.C.: Modeling and evaluating pilot performance in nextgen: Review of and recommendations regarding pilot modeling efforts, architectures, and validation studies. Technical report, Human Centered Systems Lab (2013)Google Scholar
- 13.John, B.E., Prevas, K., Salvucci, D.D., Koedinger, K.: Predictive human performance modeling made easy. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2004, pp. 455–462. ACM, New York (2004)Google Scholar
- 14.Anderson, J.R., Lebiere, C.J. (eds.): The Atomic Components of Thought. Lawrence Erlbaum Associates, Mahwah (1998)Google Scholar
- 15.Corker, K.M., Smith, B.R.: An architecture and model for cognitive engineering simulation analysis: Application to advanced aviation automation. In: Proceedings of AIAA Computing in Aerospace 9 Conference, San Diego, CA, 21 October 1993Google Scholar
- 16.Wickens, C.D., Helleberg, J., Goh, J., Xu, X., Horrey, W.J.: Pilot task management: testing an attentional expected value model of visual scanning. Technical report, NASA Ames Research Center Moffett Field, CA (2001)Google Scholar
- 18.Frische, F., Osterloh, J.-P., Lüdtke, A.: Simulating visual attention allocation of pilots in an advanced cockpit environment. In: Modelling and Simulation (MODSIM) World Conference & Expo, Hampton, Virginia, USA, 13–15 October 2010Google Scholar