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Relations between cognitive load and user experience. Measuring via eye-tracker

 
: Breiner, Kai; Jung, Jessica; Hess, Steffen

Berns, Karsten (Ed.); Schindler, Christian (Ed.); Dreßler, K. (Ed.); Jörg, B. (Ed.); Kalmar, Ralf (Ed.); Zolynski, G. (Ed.) ; Commercial Vehicle Alliance -CVA-, Kaiserslautern:
Commercial vehicle technology 2014 : Proceedings of the 3rd Commercial Vehicle Technology Symposium (CVT 2014), March 11-13, 2014, University of Kaiserslautern, Kaiserslautern, Germany
Aachen: Shaker, 2014
ISBN: 978-3-8440-2573-6
pp.396-405
Commercial Vehicle Technology Symposium (CVT) <3, 2014, Kaiserslautern>
English
Conference Paper
Fraunhofer IESE ()
user experience; experiment; eye-tracking; cognitiv load; n-back; driving study; mental effort

Abstract
This paper introduces motivation and background of our current research on exploring measurement of mental workload or cognitive load (CL) via eye-tracking in real-life driving situations as well as simulated driving environments. Therefore, we designed an experiment to systematically induce different levels of CL while driving on a test track (primary task). As a secondary task, the n-back task was applied. Furthermore, the usage of a mobile phone while driving was experimentally varied to induce further inattention into the driver resulting in six different driving-tasks to perform. Measurement was done via eye-tracking to achieve an objective and continuous measurement that goes beyond traditional subjective measurements such as questionnaires like SAM or PANAS. The aim of the pilot study reported in this paper was to explore if the experimental setting is applicable, if the measurement and data collection was feasible, and if it is possible to discriminate between the different levels of CL. The results of the pilot study show that there are different strategies to cope with CL in driving tasks. We conclude that CL impacts user experience (UX) in a way, which is determined by the coping strategy as well as contextual factors. Further research is challenged by how to experimentally induce different factors of UX, and integrate the UX factors with CL effectively.

: http://publica.fraunhofer.de/documents/N-324248.html