Evaluation of Visualisation of Scanpath Trend Analysis (ViSTA) Tool

Authors : Şükrü ERASLAN, Serkan Karabulut, Mehmet Can Atalay, Yeliz YEŞİLADA

Pages : 373-383

Doi:10.17694/bajece.490601

View : 11 | Download : 6

Publication Date : 2019-10-30

Article Type : Research Paper

Abstract :Eye tracking plays a key role in user behaviour understanding and usability studies. We previously proposed an algorithm called STA insert ignore into journalissuearticles values(Scanpath Trend Analysis); that analyses multiple individual scanpaths on a web page to discover their trending path in terms of the areas of interest insert ignore into journalissuearticles values(AOIs);. This algorithm provides the most representative path of multiple users and compared to other algorithms insert ignore into journalissuearticles values(i.e., provides the most similar path to individual scanpaths);. However, its current implementation has no graphical user interface and provides a sequence of characters that represent AOIs. Some external modules should also be installed in advance to run it. In our previous work, we presented the first web-based visualisation tool for the STA algorithm called ViSTA along with its initial evaluation. This tool allows to visualise individual scanpaths on a particular web page with gaze plots, visually draw AOIs, apply the STA algorithm, and visualise the result of the algorithm. In this paper, we present the extended version of ViSTA with a follow up user evaluation. The first version of ViSTA uses the STA algorithm which identifies trending AOIs based on all individual scanpaths. However, the extended one uses the STA algorithm with the tolerance level parameter which means trending elements can be identified based on a subset of individual scanpaths for discovering a more representative path. Both of our initial and follow up evaluations show that the workload in terms of NASA Task Load Index insert ignore into journalissuearticles values(TLX); is lower with ViSTA compared to the current implementation of the STA algorithm.
Keywords : Eye Tracking, Areas of Interest, Web Pages, Trending Path, Web based, User Interface