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http://dx.doi.org/10.5516/NET.04.2013.701

A QUALITATIVE METHOD TO ESTIMATE HSI DISPLAY COMPLEXITY  

Hugo, Jacques (Idaho National Laboratory, Human Factors Department)
Gertman, David (Idaho National Laboratory, Human Factors Department)
Publication Information
Nuclear Engineering and Technology / v.45, no.2, 2013 , pp. 141-150 More about this Journal
Abstract
There is mounting evidence that complex computer system displays in control rooms contribute to cognitive complexity and, thus, to the probability of human error. Research shows that reaction time increases and response accuracy decreases as the number of elements in the display screen increase. However, in terms of supporting the control room operator, approaches focusing on addressing display complexity solely in terms of information density and its location and patterning, will fall short of delivering a properly designed interface. This paper argues that information complexity and semantic complexity are mandatory components when considering display complexity and that the addition of these concepts assists in understanding and resolving differences between designers and the preferences and performance of operators. This paper concludes that a number of simplified methods, when combined, can be used to estimate the impact that a particular display may have on the operator's ability to perform a function accurately and effectively. We present a mixed qualitative and quantitative approach and a method for complexity estimation.
Keywords
Information Complexity; Information Density; Semantic Complexity; Human Factors;
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1 Gilmore, W. E., Gertman, D.I., and Blackman, H.S. (1989). The User-Computer Interface in Process Control, Academic Press, San Diego.
2 Heise, D. R. (1965). "Semantic differential profiles for 1,000 most frequent English words." Psychological Monographs, 70 8:
3 Liu, Xiaofei (2010). Automatic analysis of syntactic complexity in second language writing. International Journal of Corpus Linguistics, 15(4):474-496.   DOI
4 Lohrenz, M.C., Trafton, J.G., Beck., M.R., and Gendron, M.L: (2009). "A model of clutter for complex multivariate, geospatial displays." Human Factors, 51(1) 90-101.   DOI
5 Mack, M. L., and Oliva, A. (2004). "Computational estimation of visual complexity". Paper presented at the 12th Annual Object, Perception, Attention, and Memory Conference. Minneapolis, Minnesota.
6 Nees, M.A. and Walker, B.N., (2008). "Data density and trend reversals in auditory graphs: Effects on point-estimation and trend-identification tasks". ACM Transactions. Appl. Percpt. 5, 3, Article 13 (August 2008), 24 pages. DOI.
7 Ngo, D.C.L. and Byrne, J.G.,(2001). "Another look at a model for evaluating interface aesthetics." International Journal of Applied Mathematics and Computer Science. Vol.11, No.2, 515-535.
8 Reddy, L. and VanRullen, R. (2007). "Spacing affects some but not all visual searches: Implications of theories of attention and crowding." Journal of Vision, 7(2), 1-17.
9 Rosenholtz, R., (2000). "Significantly different textures: A computational model of pre-attentive texture." ECCV.
10 Rosenholtz, R., Li, Y., and Nakano, L., (2007). "Measuring Visual Clutter," Journal of Vision, 2007, 7(2):17, 1-22
11 Sanderson, P.M., Flach, J.M., Buttigieg, M.A., and Casey, E. J., (1989). "Object displays do not always support better integrated task performance." Human Factors, 31, 2, 183- 198.   DOI
12 Shepard, R. N. and Cooper, L.A. (1982). Mental images and their transformations. Cambridge, MA/London, England: MIT Press.
13 Tufte, E.R., (2001). Visual display of quantitative information (2nd Ed). Graphics Press.
14 Walker, G.H., Stanton, N.A., Salmon, P.M., Jenkins, D.P. and Rafferty, L. (2010). "Translating concepts of complexity to the field of ergonomics." Ergonomics, 53(10), 1175 - 1186.   DOI   ScienceOn
15 Ware, C. (2000) Information Visualization: Perception in Design. Morgan Kauffmann, NY: NY,
16 Webb, N.L., 1999, Alignment Between Standards and Assessment, University of Wisconsin Centre for Educational Research.
17 Beck, M.R., Lohrenz, M.C., & Trafton, J.G. (2010). Measuring search efficiency in complex visual search tasks: Global and local clutter. Journal of Experimental Psychology: Applied, 16(3), 238-250   DOI   ScienceOn
18 Xing, J. (2004). Measures of Information Complexity and the Implications for Automation Design. FAA Civil Aerospace Medical Institute. DOT/FAA/AM-04/17.
19 Banks, W.W., and Weimer, J., (1992). Effective Computer Display Design, Prentice Hall, NY.
20 Ben-Shachar, M., Palti, D., and Grodzinsky, Y., (2004). "Neural correlates of syntactic movement: converging evidence from two fMRI experiments." NeuroImage, 21(4), 1320-1336.   DOI   ScienceOn
21 Bertin, J., (2011). Semiology of Graphics: Diagrams, Networks, Maps. ESRI Press, Redlands, CA.
22 Bonebright, T.L., Nees, M.A., Connerly, T.T., and McCain, G.R. (2001). "Testing the effectiveness of sonified graphs for education: A programmatic research project." Proceedings of the International Conference on Auditory Display (ICAD2001), Espoo, Finland. 62-66.
23 Brennan, J. and Pylkkanen, L., (2012). "The time-course and spatial distribution of brain activity associated with sentence processing." NeuroImage, 60: 1139-1148.   DOI   ScienceOn
24 Brennan, J., and Pylkkanen, L., (1988). "Behavioural and MEG Measures of Two Different Types of Semantic Complexity." Language and Cognitive Processes, vol. 25, no. 6, pp. 777-807, 2010   DOI   ScienceOn
25 Burleson, B.R., and Waltman, M.S. (1988). "Cognitive complexity: Using the Role Category Questionnaire measure." In C. H. Tardy (Ed.), A handbook for the study of human communication: Methods and instruments for observing, measuring, and assessing communication processes (pp. 1-35). Norwood, NJ: Ablex.
26 Ferreira, F., and Clifton Jr., C. (1986). "The Independence of Syntactic Processing." Journal of Memory and Language, 25(3), 348-368   DOI   ScienceOn
27 Caplan, D., Vijayan, S., Kuperberg, G., West, C., Waters, G., Greve, D, (2002). "Vascular responses to syntactic processing: Event-related fMRI study of relative clauses." Human Brain Mapping, 15(1), 26-38.   DOI   ScienceOn
28 Cummings, M.L., Sasangohar, F., Thornburg, K.M., Xing, J. and D'Agostino, A. (2010). "Human-System Interface Complexity and Opacity. Part I: Literature Review." NRC Report. Massachusetts Institute of Technology.
29 Faichney, J. (2004), Content-based retrieval of digital video. Doctoral thesis, Griffith University.
30 Frazier, L. and Fodor, J.D. (1978) "The sausage machine: A new two stage parsing Model". Cognition, Volume 6 pp 291-325.   DOI   ScienceOn
31 Gennari, S. and Poeppel, D. (2003). Processing correlates of lexical semantic complexity, Cognition, 89(1), B27-41.   DOI   ScienceOn
32 Gertman, D. (2012). "Complexity: Application to Human Performance Modeling and HRA for Dynamic Environments," Proceedings for Instrumentation Control and Intelligent Systems (ICIS), Salt Lake City UT.
33 Gibson, E. (1998). "Linguistic complexity: Locality of syntactic dependencies." Cognition, 68, 1-76.   DOI   ScienceOn