Maria Dragunova
Robert Moro
Maria Bielikova
ABSTRACT
Findability belongs to key aspects of a webpage usability. When testing findability, the measured task times result not only from the design of a web page, but are influenced also by the individual differences in the participants? abilities, such as their visual search ability. In order to measure this ability, we designed a calibration procedure consisting of a visual search task containing Web icons. In this poster paper, we present results of a quantitative eye tracking study with 45 participants comparing the designed visual search task to the standard conjunction search with respect to the reaction time, number of fixations as well as the used search strategies. The results show that searching for icons is a harder task eliciting more fixations and longer reaction times. In addition, it allows us to differentiate the visual search ability of the users as indicated by the differences in reaction times and search strategies.
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Measuring Visual Search Ability on the Web
- Jennifer Cardello. 2014. Low findability and discoverability: Four testing methods to identify the causes. Retrieved January 16, 2017 from https://www.nngroup.com/articles/navigation-ia-testsGoogle Scholar
- Cristina Conati, Giuseppe Carenini, Enamul Hoque, Ben Steichen and Dereck Toke. 2014. Evaluating the impact of user characteristics and different layouts on an interactive visualization for decision making. Comput Graph Forum 33, 3: 371--380.Google ScholarCross Ref
- Patrik Hlavac. 2016. Impact of characteristics of individuals on evaluating the quantitative studies. In Ext. Proc. of the 24th Conf. on User Modeling, Adaptation, and Personalization (UMAP '16). CEUR-WS 1618, 4.Google Scholar
- Tomas Juhaniak, Patrik Hlavac, Robert Moro, Jakub Simko and Maria Bielikova. 2016. Pupillary response: Removing screen luminosity effects for clearer implicit feedback. In Ext. Proc. of the 24th Conf. on User Modeling, Adaptation, and Personalization (UMAP '16). CEUR-WS 1618, 2.Google Scholar
- Krzysztof Krejtz, Andrew T. Duchowski and Arzu Çöltekin. 2014. High-level gaze metrics from map viewing: Charting ambient/focal visual attention. In Proc. of the 2nd Int. Workshop in Eye Tracking for Spatial Research (ET4S). CEUR-WS 1241, 37--41.Google Scholar
- Peter Moville. 2004. User experience design. Retrieved January 16, 2017 from http://semantic studios.com/user_experience_design/Google Scholar
- Jeremy M. Wolfe. 1998. Visual search. In Attention, Harold Pashler (Ed.). Psychology Press, 13--73.Google ScholarCross Ref
- Jeremy M. Wolfe, Evan M. Palmer and Todd S. Horowitz. 2010. Reaction time distributions constrain models of visual search, Vision Res 50, 14: 1304--1311.Google ScholarCross Ref
Index Terms
- Measuring Visual Search Ability on the Web
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