Abstract
One hundred and nineteen military aviators were tasked with developing route plans for directing multiple Unmanned Aerial Vehicles to search for targets with different values and probabilities of being found. Target icon visualizations were manipulated on the planning display’s map, such that half the trials included either enhanced or simple icons. Plan quality performance was not impacted by icon type, but participants developed plans 11% faster with enhanced icons. Additionally, neither maximum pupil dilation nor mean pupil dilation, measured during planning, were statistically different between icon types, signifying similar levels of mental effort when interacting with either icon. Fixation analyses revealed that enhanced icons increased the proportion of time spent looking at the map and decreased gaze transition entropy, thus indicating more deterministic scan patterns. These findings demonstrate how augmenting performance analyses with eye tracking metrics provides a more complete understanding of how visualizations affect a user’s interface experience.
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References
Coyne, J., Sibley, C., Monfort, S.: Assessing situation awareness in an unmanned vehicle control task: a case for eye tracking based metrics. In: Advances in Aviation Psychology, vol. 2, pp. 217–236. Routledge, Abingdon (2017)
Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Advances in Psychology, vol. 52, pp. 139–183. North-Holland (1988)
Endsley, M.R.: Situation awareness global assessment technique (SAGAT). In: Proceedings of the National Aerospace and Electronics Conference, pp. 789–795. Institute of Electrical and Electronics Engineers, New York (1988)
Crandall, B., Klein, G., Klein, G.A., Hoffman, R.R.: Working Minds: A Practitioner’s Guide to Cognitive Task Analysis. Mit Press, Cambridge (2006)
Kahneman, D., Beatty, J.: Pupil diameter and load on memory. Science 154(3756), 1583–1585 (1966)
Hess, E.H., Polt, J.M.: Pupil size in relation to mental activity during simple problem-solving. Science 143(3611), 1190–1192 (1964)
Beatty, J., Lucero-Wagoner, B.: The pupillary system. In: Cacioppo, J.T., Tassinary, L.G., Berntson, G.G. (eds.) Handbook of Psychophysiology, 2nd edn, pp. 142–162. Cambridge University Press, Cambridge (2000)
Pincus, S.: Approximate entropy (ApEn) as a complexity measure. Chaos Interdisc. J. Nonlinear Sci. 5(1), 110–117 (1995)
McKinley, R.A., McIntire, L.K., Schmidt, R., Repperger, D.W., Caldwell, J.A.: Evaluation of eye metrics as a detector of fatigue. Hum. Factors 53(4), 403–414 (2011)
Brown, N., Coyne, J., Sibley, C., Foroughi, C.: Human performance in the simulated multiple asset routing testbed (SMART): an individual differences approach. In: Boring, R. (ed.) Advances in Human Error, Reliability, Resilience, and Performance, AHFE 2019, Advances in Intelligent Systems and Computing, vol 956. Springer, Cham (2020)
Coyne, J.T., Foroughi, C.K., Brown, N.L., Sibley, C.M.: Evaluating decision making in a multi-objective route planning task. In: Proceedings of the Human Factors and Ergonomic Society Annual Meeting, vol. 62, pp. 217—221 (2018)
Coyne, J., Moclaire, C., Brown, N., Foroughi, C., Sibley, C.: Normative interpupillary distance data reduces pupil size noise in a remote eye tracking system. In: Proceedings of the 20th International Symposium on Aviation Psychology, Dayton, OH (2019)
Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., Van de Weijer, J.: Eye Tracking: A Comprehensive Guide to Methods and Measures. OUP Oxford, Oxford (2011)
Borchers, H.: pracma: practical numerical math functions. R Package Vers. 1(3) (2015)
Spedicato, G.A., Kang, T.S., Yalamanchi, S.B., Yadav, D., Cordón, I.: The markovchain Package: a Package for Easily Handling Discrete Markov Chains in R (2016)
Acknowledgments
The Office of Naval Research funded this work. The authors would like to thank Dr. Jeffrey Morrison, Program Officer for the Command Decision Making (CDM) program, for his continued support.
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Sibley, C., Foroughi, C., Brown, N., Drollinger, S., Phillips, H., Coyne, J. (2021). Augmenting Traditional Performance Analyses with Eye Tracking Metrics. In: Ayaz, H., Asgher, U. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1201. Springer, Cham. https://doi.org/10.1007/978-3-030-51041-1_17
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