{"id":184,"date":"2016-02-02T12:45:36","date_gmt":"2016-02-02T12:45:36","guid":{"rendered":"http:\/\/www.pewe.sk\/uxi\/?page_id=184"},"modified":"2020-06-26T08:32:41","modified_gmt":"2020-06-26T06:32:41","slug":"studies-and-experiments","status":"publish","type":"page","link":"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/","title":{"rendered":"Studies and Experiments"},"content":{"rendered":"<h2>Spring 2019\/2020<\/h2>\n<ul>\n<li>Jakub Kubanyi: <a href=\"https:\/\/docs.google.com\/document\/d\/1S74T2lfOK-p0gWWUbM1ABXerN81Wo3fY0WePYeLDno0\/edit?usp=sharing\">Analysis of gaze patterns based on user interaction in navigation tasks<\/a><\/li>\n<li>Marek Otruba: <a href=\"#part-otruba2019-10\">Automatic detection of usability problems<\/a><\/li>\n<li>Jozef Melicher\u010d\u00edk: <a href=\"#part-melichercik2020-02\">Navigation skill level classification<\/a><\/li>\n<li style=\"list-style-type: none;\"><\/li>\n<\/ul>\n<h2>Autumn 2019\/2020<\/h2>\n<ul>\n<li><a href=\"#part-melichercik2020-02\">Jakub Kubanyi: <\/a><a href=\"https:\/\/docs.google.com\/document\/d\/1S74T2lfOK-p0gWWUbM1ABXerN81Wo3fY0WePYeLDno0\/edit?usp=sharing\">Analysis of gaze patterns based on user interaction in navigation tasks<\/a><\/li>\n<li>Samuel Gedera: <a href=\"#part-gedera2019-10\">Inference of user characteristics based on scanpaths<\/a><\/li>\n<li>Marek Otruba: <a href=\"#part-otruba2019-10\">Automatic detection of usability problems<\/a><\/li>\n<li>M\u00e1rius Rak: <a href=\"#part-rak2019-10\">Using EEG for UX during usability testing, master\u2019s thesis<\/a><\/li>\n<\/ul>\n<h2>Spring 2018\/2019<\/h2>\n<ul>\n<li>Michal Hucko, Matej V\u00e1lky: <a href=\"#part-hucko2018-03\">Identification of user confusion in a web application<\/a><\/li>\n<li>J\u00e1n Vnen\u010d\u00e1k, Samuel Gedera: <a href=\"#part-vnencak2019-05\">Generalization of user characteristics and modelling of FD-I user characteristic using eye-tracking<\/a><\/li>\n<li>Martin Hoang: <a href=\"#part-hoang2019-04\">Evaluation methods when comparing 2D, 3D and virtual reality<\/a><\/li>\n<li>Mark\u00e9ta Beitlov\u00e1: <a href=\"#part-beitlova2019-04\">Map reading by different users group<\/a><\/li>\n<li>Miroslav Smetana, Peter P\u00edseck\u00fd: <a href=\"#part-smetanapisecky2019-04\">Website navigation and identification of usability problems<\/a><\/li>\n<li>Filip Loja: <a href=\"#part-loja2018-11\">An alternative way of measuring user\u2019s attention to the user interface<\/a><\/li>\n<li>Partik Racsko: <a href=\"#part-racsko2019-03\">Behavioral analysis of fake news readers<\/a><\/li>\n<li>Valentin Paulen: <a href=\"#part-paulen2019-03\">Modeling user navigation on the Web<\/a><\/li>\n<li>Dominik \u0160tefani\u010dka: <a href=\"#part-stefanicka2019-03\">Identification of impact of the elements in the web application on behavior of an user<\/a><\/li>\n<li>Patrik Kov\u00e1cs: <a href=\"#part-kovacs2019-03\">Discovery of view patterns in navigational tasks on the web<\/a><\/li>\n<li>Gabriel Csikm\u00e1k: <a href=\"#part-csikmak2019-03\">Detection of gaze patterns in navigational tasks on the Web<\/a><\/li>\n<li>M\u00e1rius Rak: <a href=\"#part-rak2019-01\">Using EEG for UX during usability testing, master\u2019s thesis<\/a><\/li>\n<\/ul>\n<h2>Autumn 2018\/2019<\/h2>\n<ul>\n<li>Marek Jakab: <a href=\"#part-jakab2018-12\">The effect of contours on visual attention<\/a><\/li>\n<li>\u013dubom\u00edr Samotn\u00fd: <a href=\"#part-samotny2018-12\">Automatic categorization of users based on their web navigation<\/a><\/li>\n<li>Roderik Willinger: <a href=\"#part-willinger2018-12\">Analysis of the relationship between usability problems and long-term characteristic of the user<\/a><\/li>\n<li>Filip Loja: <a href=\"#part-loja2018-11\">An alternative way of measuring user\u2019s attention to the user interface<\/a><\/li>\n<li>Martina Han\u00e1kov\u00e1, Patrik Racsko: <a href=\"#part-hanakovaracsko2018-10\">Analysis of fake news reader&#8217;s view behaviour<\/a><\/li>\n<li>Adam Str\u00e1sky: <a href=\"#part-strasky2018-02\">Analysis of influence \u00a0of different types of dataset to express the intensity of emotion<\/a><\/li>\n<li>Michal Hucko, Matej V\u00e1lky: <a href=\"#part-hucko2018-03\">Identification of user confusion in a web application<\/a><\/li>\n<\/ul>\n<h2>Spring\u00a02017\/2018<\/h2>\n<ul>\n<li>J\u00e1n Vnen\u010d\u00e1k: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#vnencak2018-04\">Scanpath Visualization<\/a><\/li>\n<li>Michal Hucko, Matej V\u00e1lky: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#hucko2018-03\">Identification of user confusion in a web application<\/a><\/li>\n<li>Andrej Za\u0165ko:<a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#zatko2018-03\">The impact of images on user`s behavior on Web<\/a><\/li>\n<li>Martin Svr\u010dek: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#svrcek2018-03\">Eye tracking the user behavior on the Web<\/a><\/li>\n<li>M\u00e1ria Drag\u00fa\u0148ov\u00e1, Matej \u010cervenka: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#dragunova2018-03\">Identifying users characteristics by eye tracking analysis<\/a><\/li>\n<li>Martin \u0160idlo: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#sidlo2018-03\">Identification of usability problems on web sites using the eye-tracker<\/a><\/li>\n<li>Ondrej Kipila: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#kipila2018-03\">Detection of User\u2019s Intent on the Web based on Eye-tracking Method<\/a><\/li>\n<li>J\u00e1n Trimel:<a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#trimel2018-02\"> User experience and work with control devices<\/a><\/li>\n<li>Adam Str\u00e1sky: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#strasky2018-02\">Analysis of influence \u00a0of different types of dataset to express the intensity of emotion<\/a><\/li>\n<li>Patrik Gajdo\u0161\u00edk: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#gajdosik2018-02\">Eye Tracking Using Deep Neural Networks<\/a><\/li>\n<\/ul>\n<h2>Autumn 2017\/2018<\/h2>\n<ul>\n<li>Mat\u00fa\u0161 Tund\u00e9r: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#tunder2018-02\">Analysis of source code reading<\/a><\/li>\n<li>Peter Ga\u0161par:\u00a0<a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#gaspar2018-01\">Analysis of Influcence of Visual Stimuli on Movies Selection<\/a><\/li>\n<li>Martin Mokr\u00fd: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#mokry2017-11\">Identification of the user familiarity with Web domain, based on patterns in eyetracking data<\/a><\/li>\n<li>Martina Redajov\u00e1: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#redajova2017-11\">Automatic recognition of user characteristics<\/a><\/li>\n<li>Jakub Kubanyi: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#kubanyi2017-11\">The relation of gaze fixations and user\u2019s skill in the digital s<\/a><\/li>\n<li>D\u00e1niel Papp: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#papp2017-11\">Visual attention and saliency mapping on web page elements<\/a><\/li>\n<li>Filip \u0160andor: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#sandor2017-11\">Personalized search by using eye tracking to better identifying the user query<\/a><\/li>\n<li>Viktor Ko\u0161\u0165an: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#kostan2017-10\">Facial engagement recognition using sequential analysis<\/a><\/li>\n<li>Mat\u00fa\u0161 G\u00e1sp\u00e1r: <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#gaspar2017-10\">Eye-tracking of user while reading source codes<\/a><\/li>\n<li>Bronislava Strn\u00e1delov\u00e1 (FSaEV UK):\u00a0<a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#strnadelova2017-10\">Identification of emotions by eyetracking in relation to self-criticism<\/a><\/li>\n<li>J\u00e1n Hanko:\u00a0<a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments\/#hanko2017-11\"><span style=\"font-weight: 400;\">The relation of gaze fixations and user&#8217;s skill in the digital space<\/span><\/a><\/li>\n<\/ul>\n<p><em>please insert here the entry according to the <a href=\"http:\/\/www.pewe.sk\/uxi\/studies-and-experiments-instructions\/\">instructions<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-melichercik2020-02\"><em> Navigation skill level classification<\/em><\/h3>\n<p><strong>Date:<\/strong><em> Februar 2020<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Jozef Melicher\u010d\u00edk<\/em><br \/>\n<strong>Supervisor: <\/strong><em>Ing. Patrik Hlav\u00e1\u010d<\/em><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The experiment was preceded by a pilot experiment: link<br \/>\nThe aim of the diploma thesis is to classify the level of navigation skills from eyetracker data, mouse and web records. The following hypotheses have emerged from the analysis, which need to be verified:<\/p>\n<ul>\n<li>Web user scanpaths vary based on their navigational skills<\/li>\n<li>Web users can be classified according to their navigational skills<\/li>\n<li>User Navigation Skill Level Model can achieve an accuracy of at least 80%<\/li>\n<li>The Gaze AoI transition metric will have a high impact on the classification of the resulting class<\/li>\n<\/ul>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1ci43KVeWmHEz0UMT3gaP16L5D9bU3dYYCGn_R8BhtOc\/edit?usp=sharing\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-gedera2019-10\"><em>Inference of user characteristics based on scanpaths<\/em><\/h3>\n<p><strong>Date:<\/strong><em> October 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Samuel Gedera<\/em><br \/>\n<strong>Supervisor: <\/strong><em>Ing. R\u00f3bert M\u00f3ro, PhD.<\/em><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Filling in questionnaires takes a lot of time to evaluate user characteristics. It has been shown, that it is possible to determine the values of individual user characteristics on the basis of collected data from eye-tracker. As a result of his eye movements, the values of his individual user characteristics can then be inferred. In a domain like an e-commerce, this knowledge is important, as a graphical interface can be tailored to the user based on these values, which can lead to a reduction in task time.<br \/>\nIn our work, we focus on inference of user characteristics, based on data, that is collected by the eye-tracker. There are a lot of work on this issue, but the accuracy of inference of the user characteristics are different, which is caused by different methods in inferring this characteristics. It should be a different user model, where researchers try to combine different features or the algorithm itself, which is based on this mode. In our work, we want to focus on the user model, where, in addition to standard features such as fixation length, fixation number, and more, we want to extend this model with scanpath that could improve accuracy in inference of user characteristic.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1w2DZ2C12lIyfmEsVsLMTskq-1pJLIKhf0CsuryvmQzY\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-otruba2019-10\"><em> Automatic detection of usability problems<\/em><\/h3>\n<p><strong>Date:<\/strong><em> October 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Marek Otruba<\/em><br \/>\n<strong>Supervisor: <\/strong><em>doc. Ing. Jakub \u0160imko, PhD.<\/em><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Web usability has been a common term in recent years. This is one of the most important conditions determined by webmasters. Therefore, besides the quality and functionality of the system, great emphasis is placed on the user experience. Simplicity and troublefree form the basis for a usable system. Internet is used by skilled and less skilled users, that\u2019s why this requirement should be met. Some creators neglect this condition and therefore often create disarranged websites where the user can hardly navigate. User testing represents an option how to avoid usability problems. Another problem we encounter is that manual website evaluation is very laborious and time-consuming. Therefore, our goal is to create a method that automatically identifies usability issues, thereby reducing evaluation time. Using metrics, we\u2019ll create and train a model to identify usability problems. We will use two different tests for the experiment. In one where the usability problems will be eliminated and the other where these problems will be contained on the website.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1p6V8vpDNycYwYWQvsRw9UVroDmc8y8hj5vY5lZ4xJ6k\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-rak2019-10\"><em> Using EEG for UX during usability testing, master\u2019s thesis<\/em><\/h3>\n<p><strong>Date:<\/strong><em> October 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>M\u00e1rius Rak<\/em><br \/>\n<strong>Supervisor: <\/strong><em>Mgr. Jozef Tvaro\u017eek, PhD.<\/em><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Epxeriment for purposes of master\u2019s thesis. Aim of experiment is to verifiy possibility of using EEG for usability testing. EEG should help determine emotional valence and mental workload during software use.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1JTeGkXk842-wVo8TFO3v-gSf4mT4PFaOUac9XrtJM9M\/edit#heading=h.vm0fs2shusjr#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-vnencak2019-05\"><em>Generalization of user characteristics and modelling of FD-I user characteristic using eye-tracking<\/em><\/h3>\n<p><strong>Date:<\/strong><em> May 2019 &#8211; May 2020<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>J\u00e1n Vnen\u010d\u00e1k, Samuel Gedera<\/em><br \/>\n<strong>Supervisor: <\/strong><em>Ing. R\u00f3bert M\u00f3ro, PhD.<\/em><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>User characteristics can affect the success and effectiveness of performing tasks on the system. Based on the user model, it is possible to customize system to user requirements or target information that might be useful. User characteristics also play a role in system usability testing, where knowledge of these characteristics helps us to reduce distortion of test results.<br \/>\nIn our work we deal with the effect of the user personality traits to solving typical tasks in the e-shop using eye-tracking. The aim of our work is to identify features that are related to individual personality traits and then select and design those features that are significant within various online stores. Based on findings, we want to create a model which will be able to automatically identify user personality trait independently of the page interface.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1w2DZ2C12lIyfmEsVsLMTskq-1pJLIKhf0CsuryvmQzY\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-hoang2019-04\"><em>Evaluation methods when comparing 2D, 3D and virtual reality<\/em><\/h3>\n<p><strong>Date:<\/strong><em> April 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Martin Hoang<\/em><br \/>\n<strong>Supervisor: <\/strong><em>Ing. Juraj Vinc\u00far<\/em><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Developing a software, software engineers usually create a source code using a keyboard and a mouse. The programmer can see his code on a limited number of 2D screens. Amongst programmers, this traditional approach has been quite common for last several decades. However, this kind of approach ignores the possibilities of human movement and spatial perception, which are provided by new technologies used for displaying of virtual reality. It enables us to display 3D area, opening new avenues to adopt a new stance on software development, it brings us a much bigger work area and the third dimension for work. Virtual reality can be accessed through various devices, such as OculusRift or HTC Vive. It is not possible programming directly in virtual reality,another type of programming supporting work in virtual reality must be used.It can be replaced by block-based programming that has also an educational potential. We believe that the appropriate combination of virtual reality and block-based programming can help to create an educational environment. For even more effective immersion in virtual reality, we will use the principles of gamification that has also an motivational effect.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1dYOjsaCJXfJLhHPImLKfgvJvjAz6Driw4r8jYV8cpCA\/edit?ts=5ccfd5c7\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-beitlova2019-04\"><em>Map reading by different users group<\/em><\/h3>\n<p><strong>Date:<\/strong><em> April 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Mark\u00e9ta Beitlov\u00e1<\/em><br \/>\n<strong>Supervisor: <\/strong><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The aim of the project is to find out whether different groups of map readers reporting while reading maps and strategies. Define possible factors that influence map reading based on cartographic communication models. Three groups of respondents, map authors, cartographers and non-cartographers will participate in the survey. The first two groups are represented by students of the Department of Geoinformatics of Palack\u00fd University in Olomouc. The third group are students of FIIT STU Bratislava. The maps were created by students of the Department of Geoinformatics within the cartography. The experiment is divided into two parts. In the first, free viewing contains 22 maps showed for 12 s. In the second part, respondents solve selected tasks than in the previous section. This experiment does not contain any questionnaire.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1TLVY9zZqrHDHZzOUqiqkw8iVWea5Fdz7WlLqTZTsrdM\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-smetanapisecky2019-04\"><em>Website navigation and identification of usability problems<\/em><\/h3>\n<p><strong>Date:<\/strong><em> April 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Miroslav Smetana, Peter P\u00edseck\u00fd<\/em><br \/>\n<strong>Supervisor: <\/strong>Ing. Eduard Kuric, PhD.<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The goal of the experiment is to record data from interaction with the website&#8217;s user interface using peripheral devices such as a mouse and keyboard, to record the gaze of users of the website, as well as to collect data representing the emotional state of the experiment participants. Data is collected within the project for the purpose of further analysis and verification of the methods proposed in the diploma theses.<br \/>\nThe methods of the theses are automatic identification of usability problems and estimation of participants&#8217; navigation skills. Data is recorded while performing targeted tasks on two web portals. During the experiment, experiment participants will perform the tasks of finding information on the aforementioned portals. Data collection is ensured by the existing infrastructure developed at the faculty.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1ZoNE3ffmpyTHS5SXNE3wHDOnXZmlrP32djF-Vby-6qM\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-racsko2019-03\"><em>Behavioral analysis of fake news readers<\/em><\/h3>\n<p><strong>Date:<\/strong><em> March 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Patrik Racsko<\/em><br \/>\n<strong>Supervisor: <\/strong>Ing. Jakub \u0160imko, PhD.<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The goal of our experiment is to find out the common and different behavioral features of experienced and inexperienced users when reading fake news. We will focus on experimental data collection, where we\u2019ll find out how users process fake news which are consistent and not consistent with their opinion. Next how is their choice influenced by different categories and what behavioral patterns are made by experienced and inexperienced users.<br \/>\nWe have created a fake environment, that emulates one of the most famous social platforms, Facebook. We added 50 articles from different areas of interest. Some of them are fake news and some of them are true. Users will be able to respond using the buttons: Definitely true, Rather true, Rather false, Definitely false, Can\u2019t say.<br \/>\nThe experiment will take place in two sessions, while the first session focuses on inexperienced users(high school students) and the second session on experienced users(hoax hunters). For experienced users there will be an interview in which we\u2019ll focus on their opinion they have created during the experiment. This division and subsequent comparison of behavioral features will help us to evaluate the differences in these groups.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/17yH22hYiMOsFbQvFkhTNivPJrsaj9p_jy7hbkuMzMdc\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-paulen2019-03\"><em>Modeling user navigation on the Web<\/em><\/h3>\n<p><strong>Date:<\/strong><em> March 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Valentin Paulen<\/em><br \/>\n<strong>Supervisor: <\/strong>Ing. Patrik Hlav\u00e1\u010d<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Popularity and importance of World Wide Web is constantly rising. Web pages have become an important and usually preferred source of knowledge. Web page design and applied navigation methods significantly affect the way users interact with the page. Observing and evaluating such behavior is crucial in the process of improving Web pages and customizing them to the needs of their users.Studying behavior of users on the Web usually consist of exploring the patterns in the data from UX experiment. Finding required knowledge in loads of data can be challenging, difficult and time-consuming task.<br \/>\nTo simplify and refine the process of understanding navigational behavior, appropriate model can be used to perform analysis and comparison of gathered data. The result is important knowledge about the page itself and about the users that participated in the experiment. Comparing solutions of navigational tasks on the page between users can reveal differences in an individual difficulty of the task. Watching changes in behavior of a concrete user in the time can uncover a progressive change of understanding the Web page navigation methods. Effectiveness of task solution can be quantified by confronting it with the Web page structure.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1KefXu8ATkXsNirR4edLQaUC4wKlILvw7fAnEoOBU568\/edit#\" target=\"_blank\" rel=\"noopener noreferrer\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-stefanicka2019-03\"><em>Identification of impact of the elements in the web application on behavior of an user<br \/>\n<\/em><\/h3>\n<p><strong>Date:<\/strong><em> March 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Dominik \u0160tefani\u010dka<\/em><br \/>\n<strong>Supervisor: <\/strong>Ing. Jakub \u0160imko, PhD.<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>This project is implemented as the bachelor thesis in cooperation with the University of Canterbury, New Zealand. The people in the university developed video-learning system that we choose as the general experiment environment. The main feature of this environment is option to contribute to video-learning process by own comments. Also in the study we are interested in impact of the elements of these comments in the video-learning web environment on behaviour of an user. The project has 2 phases. The first one is the experiment described below. The second one is after the experiment and in this phase we will process and analyse data gained during the experiment.The results of the primary goals will be communicated to the authors of the system to next development. The participants will be watching video tutorials and examples of proper presentation to improve their presentation skills in prepared video-learning system. Our goal is to identificate impact of system and helping elements on behavior of a participant.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1CaZiB9u2Xg-M-PQ3LcVPy1JoAyfcxAZYpNixQJu329g\/edit#heading=h.vm0fs2shusjr\" target=\"_blank\" rel=\"noopener noreferrer\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-csikmak2019-03\"><em>Detection of gaze patterns in navigational tasks on the Web<\/em><\/h3>\n<p><strong>Date:<\/strong><em> March 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Gabriel Csikm\u00e1k<\/em><br \/>\n<strong>Supervisor: <\/strong>Ing. Patrik Hlav\u00e1\u010d<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>In this project, our goal is to understand the user\u2019s behaviour while performing navigational tasks on the Web. We would like to examine this activity within product search process performed in the search engine. For this purpose, we proposed two types of navigational tasks:<br \/>\nFinding a concrete product (precisely specified product)<br \/>\nFinding an ideal product (generally specified product)<br \/>\nThe aim of this work is to determine, whether a type of task can have an effect on user\u2019s interaction. The experiment will be primarily focused on the impact of snippets \u201ctethered\u201d to each of search results. Role of these snippets can be important in cases, when a user does not search for a specified target &#8211; the informativness of a snippet can lead to finding of a required result.<br \/>\nDuring this study, we will work with two types of navigational tasks mentioned above. To track user behaviour, we will use technology of eye-tracking. Finally, our plan is to analyze the acquired data for our type of experiment.<\/p>\n<p><em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1S6zs2M0tNG_SMsOmt0xyULwMblwHJgHLH0QhAnZIk2g\/edit?usp=sharing\" target=\"_blank\" rel=\"noopener noreferrer\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-kovacs2019-03\"><em>Discovery of view patterns in navigational tasks on the web<\/em><\/h3>\n<p><strong>Date:<\/strong><em> March 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Patrik Kov\u00e1cs<\/em><br \/>\n<strong>Supervisor: <\/strong>Patrik Hlav\u00e1\u010d<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The experiment will focus on comparing the selected navigational mechanisms according to their effectiveness. Efficiency is defined by the number of steps required to achieve the result. In our study, we compare different variations of the given website. The variants will be distinguished according to different navigational mechanisms that they use. For comparison, we have selected the most commonly used navigation mechanisms, such as breadcrumb, sitemap, and dynamic menus. The efficiency of navigational mechanisms will be evaluated from the data obtained from the eye tracker and from the process of problem solving followed by the participants of the experiment. From the obtained data, it will be possible to evaluate the success rate of each menu type, according the level of the menu that contains the necessary knowledge for achieving the result.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1G1jdteOvhWvU1JBBpqi0JYUg2Jy0rLuAKwBqYHG_HOQ\/edit?usp=sharing\" target=\"_blank\" rel=\"noopener noreferrer\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-rak2019-01\"><em>Using EEG for UX during usability testing, master\u2019s thesis<\/em><\/h3>\n<p><strong>Date:<\/strong><em> January 2019<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>M\u00e1rius Rak<\/em><br \/>\n<strong>Supervisor: <\/strong>Jozef Tvaro\u017eek<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Epxeriment for purposes of master\u2019s thesis. Aim of experiment is to verifiy possibility of using EEG for usability testing. EEG should help determine emotional valence and mental workload during software use.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1JTeGkXk842-wVo8TFO3v-gSf4mT4PFaOUac9XrtJM9M\/edit#\" target=\"_blank\" rel=\"noopener noreferrer\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-jakab2018-12\"><em>The effect of contours on visual attention<\/em><\/h3>\n<p><strong>Date:<\/strong><em> December 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Marek Jakab<\/em><br \/>\n<strong>Supervisor:<\/strong><br \/>\n<strong>Short description: <\/strong><\/p>\n<p>Human\u2019s brain receives every second great amount of information. Such amount of bits could not be processed without previous filtering. The filter is provided by visual attention which is the main factor for being able to perceive effectively and in real time our surroundings. State-of-the-arts saliency models usually analyse intensity, color and orientation features. Our experiment focuses on the effect of object shapes and contours on visual attention. Participants of the experiment will see a set of images with silhouettes of real and abstract objects to eliminate the effect of other attention factors as much as possible. The fixation data will be used to design and evaluate new saliency model focused on object contours and shapes.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1DO6mi3-SmwYMrC2y_yb9EzmbA24N3U5I04gCc26rKv4\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-samotny2018-12\"><em>Automatic categorization of users based on their web navigation<\/em><\/h3>\n<p><strong>Date:<\/strong><em> December 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>\u013dubom\u00edr Samotn\u00fd<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Patrik Hlav\u00e1\u010d<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The aim of this work is to create an automated method of categorizing users according to their cognitive styles. That is why we need to get enough data on how users of different cognitive styles are behaving on the web. Based on these, we will design and verify a classifier that can properly assign a cognitive style to the user. It is proved that users with different cognitive style perceive and process the information provided to them differently. By automatically determining a user&#8217;s cognitive style only during his web browsing, it would be possible to start personalizing a site that would be better suited to his website perception, thereby improving his user experience and browsing speed.<br \/>\nTwo dimensions of cognitive styles were described and verified in psychological research in the past, specifically Verbal-Imager and Wholist-Analyst dimensions. At the beginning of the experiment, we will perform a short test to determine user\u2019s inclusion to these two cognitive style dimensions. The experiment will then continue with search-based tasks on the Web. These are designed to detect differences in users navigating behavior of different cognitive styles. For the classifier to work properly, it is therefore necessary to collect enough data from eye-tracking, but also multiple metrics measured by Javascript on the front-end.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1ifOp0QEPPGNN875USUTWemzHqFbwnj_1k7uJY6GDJ2U\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-willinger2018-12\"><em>Analysis of the relationship between usability problems and long-term characteristic of the user<\/em><\/h3>\n<p><strong>Date:<\/strong><em> December 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Roderik Willinger<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Martin Svr\u010dek, Ing. Jakub \u0160imko, PhD.<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>The aim of this project is to analyze how the long-term properties of the participants in testing the web affect their encounter with usability problems. Based on personality, we analyze what issues a particular group can detect with specific properties. Testing is done using the View Tracker and the subsequent viewing view analysis using existing metrics<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1kBJ0ZHFXvda75XROdXmndFAkEB26sbc6JuSE16nnPIE\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-loja2018-11\"><em>An alternative way of measuring user\u2019s attention to the user interface<\/em><\/h3>\n<p><strong>Date:<\/strong><em> November 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Filip Loja<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Eduard Kuric, PhD.<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>In this experiment, we are going to test a new method for recording a user&#8217;s gaze while browsing the web. The method is based on tracking the user&#8217;s cursor. A place on a website which a user is looking at is determined by the position of his cursor. To ensure that the user is really looking only at the place on the webpage where his cursor is located, the remaining content of the page will be blurred and only a certain area around the cursor will have focus. Although the content of the webpage will be blurred, the user will still be able to recognize the basic structural and navigational elements on the page but will not be able to read any content without moving the cursor to that location.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1qqnC702ip5WaCKan-L6QqJC7WPQNgz1Xr1LUzFmeBOk\/edit#heading=h.vm0fs2shusjr\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-hanakovaracsko2018-10\"><em>Analysis of fake news reader&#8217;s view behaviour<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>October 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Martina Han\u00e1kov\u00e1, Patrik Racsko<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Jakub \u0160mko, PhD.<br \/>\n<strong>Short description: <\/strong><\/p>\n<p>In our project we want to investigate the behaviour of users when reading true and fake news. We would like to find out some features that could be used for automatic detection of fake news. Next sentence serves us as a basis: &#8220;Everyone wants to read about things that confirm his point of view&#8221;. We decided to prepare an experiment in which we provide the participants with articles that are in line with their opinion and the ones that are in opposite. The articles could be both true and false. The important thing is that participants will have no clue what is the experiment really about.<br \/>\nIn the second part of experiment the participants should determine if the articles are true or false. Experiment will take place in two sessions. In the first session the participants will be secondary school students and in the second one hoax hunters. This division helps us to evaluate differences in identifying of fake news by common readers and experts.<br \/>\nAfter the experiment all participants fill in a questionnaire to determine their opinion on selected themes and rate of interest about that themes. The questionnaire also helps us to define which articles are in line with the conviction of the participant and which against it. Afterwards we will verify differences in behaviour of participants from collected data.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1ObCx7rZPDym7xcpALYUMxp7BG_X7I-6ls4EXnRXxVUw\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-hucko2018-03\"><em>Identification of user confusion in a web application<\/em><\/h3>\n<p><strong>Date:<\/strong> October<em> 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Michal Hucko, Matej V\u00e1lky<\/em><br \/>\n<strong>Supervisor:<\/strong> Prof. Ing. M\u00e1ria Bielikov\u00e1, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nConfusion on the web is a problem connected with web applications. Sometimes apps do not have to be complex to confuse users. Common problems may have newcomers, when accessing the app for the very first time. Ability to identify confusion can help us to give hints to users. These hints can help user to fulfil their needs. Hints can be combined to web application guides.<br \/>\nIn our work we identify and predict confusion on web application. We will make a method for this purpose, using logs from the server. Except them we concentrate on user \u00a0mouse movements, clicks, scrolling and browsing patterns which describe behaviour. We consider usage of eye-tracker data. Next we apply machine learning methods on gathered data. To confirm our method we will establish an experiment, where we will collect feedback from users. At the moment we are working on selection of appropriate way to collect these feedback. These will be used as labeled data. Our solution can be combined with production systems providing web application guides.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1sog1094lmmOw3-7xVMMJS5PRzCuMlmn0wXJLfEi-M-8\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"part-strasky2018-02\"><em>Analysis of influence \u00a0of different types of dataset to express the intensity of emotion<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>October 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Adam Str\u00e1sky<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. R\u00f3bert M\u00f3ro, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nWhen we recognize emotions using a webcam, we often look at emotions only during usability testing. We often do not recognize the extent to which individuals express their emotions and how these tools are accurate because we can not determine plausibility on the basis of comparison with the basic expression of emotions. The goal of the experiment is to obtain a range of emotions with varying degrees of differentiation and to determine if during the test the emotions will be captured to correspond with the expected results.<br \/>\nExperiment design consists of an initialization dataset, where the stimulus will consist of images, music clips and videos. We will try to create a stimulus scale for this participant and then perform a usability test. Finally, we will use retrospective verbal protocol with each participant to refine the results.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/13_6WoTCVHdeNYtFGf41jyivsM47OpDSVfbGZB44Ux9w\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"hucko2018-03\"><em>Identification of user confusion in a web application<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>March 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Michal Hucko, Matej V\u00e1lky<\/em><br \/>\n<strong>Supervisor:<\/strong> Prof. Ing. M\u00e1ria Bielikov\u00e1, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nConfusion on the web is a problem connected with web applications. Sometimes apps do not have to be complex to confuse users. Common problems may have newcomers, when accessing the app for the very first time. Ability to identify confusion can help us to give hints to users. These hints can help user to fulfil their needs. Hints can be combined to web application guides.<br \/>\nIn our work we identify and predict confusion on web application. We will make a method for this purpose, using logs from the server. Except them we concentrate on user \u00a0mouse movements, clicks, scrolling and browsing patterns which describe behaviour. We consider usage of eye-tracker data. Next we apply machine learning methods on gathered data. To confirm our method we will establish an experiment, where we will collect feedback from users. At the moment we are working on selection of appropriate way to collect these feedback. These will be used as labeled data. Our solution can be combined with production systems providing web application guides.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1sog1094lmmOw3-7xVMMJS5PRzCuMlmn0wXJLfEi-M-8\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"vnencak2018-04\"><em>Scanpath Visualization<\/em><\/h3>\n<p><strong>Date:<\/strong><em> April 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>J\u00e1n Vnen\u010d\u00e1k<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. R\u00f3bert M\u00f3ro, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nWe use a variety of software products every day, so it is important to make these products intuitive and easy to use. This is one of the reasons why eye tracking has become more popular in recent years. With eye tracking we can easily find where and how the user is looking at visual stimulus. A motivation is to search for patterns or similarities in the recorded data that allow us to identify different user interaction strategies with the interface. One of the methods to find these patterns or similarities is the visualization of eye tracking data.<br \/>\nIn our work, we analyzed existing methods of visualization of eye tracking data. We aim to find ones that are capable of supporting specific tasks in a better way then methods already implemented in commercial eye tracking software. Based on our analysis we implemented circular heat map transition diagram visualization method. The result of our work is a tool, which use this technique to visualize eye tracking data. The tool provide adjustment of the displayed data on user\u2019s demand. We want to verify how this method can help in exploratory analysis of eye tracking data.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1vSaqm3pyRJu-NGgHSwXyJXJ9bV1EU0MC5oJV-aNN4Yw\/edit#heading=h.vm0fs2shusjr\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"zatko2018-03\"><em>The impact of images on user`s behavior on Web<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>March 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Andrej Za\u0165ko<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Peter Ga\u0161par<br \/>\n<strong>Short description: <\/strong><br \/>\nIn our Bachelor thesis we study the potential of the image. There is a great number of information on the Web which is in the form of an image. Especially in online stores, images enrich products with visual aspect, which is crucial for users during the decision. We observe the behavior of the user while displaying text and image information. Recommender systems attempt to suggest items which attract the user. Nowadays, for creating recommendations, mostly text information is used. However, in some cases they can\u2019t describe the properties of the item accurately. Inclusion of images into the output of recommender\u2019s systems seems to be the way to overcome this issue and may lead to an improvement in accuracy of recommendations. \u00a0We propose a method for the evaluation of changes in user`s behavior.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1IoOTRYwmMRblJ4BJTmiLJbxHCiz4wrTssQ138L2pIgs\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"svrcek2018-03\"><em>Eye tracking the user behavior on the Web<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>March 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Martin Svr\u010dek<\/em><br \/>\n<strong>Supervisor:<\/strong> Prof. Ing. M\u00e1ria Bielikov\u00e1, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nUser behavior on the Web is affected by many various effects. Every person behave differently in different situations according their personal traits or states. However, there is also Web itself and especially the usability of the Web, which impact this behavior. Usability is therefore a subject of many studies and usability testing. There are many ways how to measure the usability. Often we are trying to reveal the visual attention of web users to understand their behavior. Nowadays, one of the best methods to reveal the visual attention is by tracking the user eye movement. Eye tracking is very interesting approach, which can help us to evaluate the overall usability of the Web. However, there are many different methods of analyzing the data from eye tracking and simultaneously there is no sufficient research in eye tracking data analysis in area of the user behavior on the Web. Reason for this is that Web is a dynamic environment and most of the actual research is directed only to static inputs like images. Our goal is to analyze the different representations of eye tracking data and different methods of analysis itself in order to determine the impact of usability on user behavior on the web.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1RluoY2nO36ErCu37VPCsbqB7PKhkaBtIF_toLDqMwG8\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"dragunova2018-03\"><em>Identifying users characteristics by eye tracking analysis<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>March 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>M\u00e1ria Drag\u00fa\u0148ov\u00e1, Matej \u010cervenka<\/em><br \/>\n<strong>Supervisor:<\/strong> Mgr. Jozef Tvaro\u017eek, PhD.<br \/>\n<strong>Short description:<\/strong><br \/>\nHuman individuality reflects on many aspects of our everyday lives and using web applications is not an exception. Problem of variablity between different users and their needs is commonly solved by personalisation to achieve the best possible usability for every user. However, human is a complex being and there are many characteristic, which should be considered when a system adaptation comes to mind. In our work, we analyze some of cognitive characteristics \u2013 working memory capacity, visual search and verbal-imagery dimension of cognitive styles. We propose to consider these characteristics when searching in e-catalog, which is a common structure in e-shop applications. Besides analysis of characteristics, we also focus on identifying tasks in e-commerce environment using eye-tracker.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1WvZf1gXyMzE9RHYG0Hgk-yH2VhWNKXaDGs1X0zn5Yrg\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"sidlo2018-03\"><em>Identification of usability problems on web sites using the eye-tracker<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>March 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Martin \u0160idlo<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Eduard Kuric, PhD.<br \/>\n<strong>Short description: <\/strong>Lately, usability is more discussed in the field of information technologies. Creators of the systems realized, that user experience is a huge part of a product and has a significant impact on the usage. The most effective way, how to evaluate websites, is to use user testing methods. Evaluating of such methods is a long-lasting process. Goal of this work is to shorten this time and suggest potential usability problems without a need of evaluating each user separately. In our work, we want to create models to predict such problems on a website, based on its components. In order to be able to build it, we need to train them. For this purpose, we have to gain enough data. We are using approach of a previous work of Pang et al. [1]. They have been directing user visual flow on a website. We want to use this approach with some modification and user labeling according to their cognitive abilities in order to automatically identify usability problems on websites.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1OixK20os_kPUT7eB9jr9DygDG2XGj8If7IpO5TBEd-0\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"kipila2018-03\"><em>Detection of User\u2019s Intent on the Web based on Eye-tracking Method<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>March 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Ondrej Kipila<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Jakub \u0160imko, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nThe characteristics of the user are are very useful information in information systems. If the information system is able to automatically detect the user\u2019s characteristics (eg. mood, interest, fatigue, personality characteristics, capacity short-term memory), can use this information to adapt its functionality in such a way that as far as possible meet the needs of the user. An example would be automatic content recommendation. Another option is the use of prediction of his other activities and results in the system.<br \/>\nOne way of identifying a characteristic of a user uses the tracking of user activity in the system (eg. Clicks, scrolling, text entry). Records of these activities can be further combined with monitoring a user\u2019s perspective in the implementation of these activities. Other data usable to create a user model is the size of the pupil.<br \/>\nIn this master\u2019s thesis we deal with the prediction of the user\u2019s intention (goal) when working with a web page, namely when working with an online shop. The aim of this thesis is to create a predictive model that analyzes the behavior and the user\u2019s sight and predicts the intent in real time.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1uUKNEll7yn5buPDSMWyjwUXtnlnIlT6FqNMn6xbRT-s\/edit?usp=sharing\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"trimel2018-02\"><em>User experience with web browsing, and the usage of control devices<br \/>\n<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>February 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>J\u00e1n Trimel<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. Peter Kr\u00e1tky<br \/>\n<strong>Short description: <\/strong>In this experiment we are going to develop a method of estimating user\u2019s skill in web browsing using data from monitoring the mouse and the keyboard. We determine the user\u2019s level of experience using questionnaires. Then we find a common pattern for experienced and novice users from their mouse, keyboard usage and visual fixation.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1-Cuzzt6c7woQlEG0gKHG500TWtb-cPZ9AME3kqRMc3k\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"strasky2018-02\"><em>Analysis of influence \u00a0of different types of dataset to express the intensity of emotion<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>February 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Adam Str\u00e1sky<\/em><br \/>\n<strong>Supervisor:<\/strong> Ing. R\u00f3bert M\u00f3ro, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nWhen we recognize emotions using a webcam, we often look at emotions only during usability testing. We often do not recognize the extent to which individuals express their emotions and how these tools are accurate because we can not determine plausibility on the basis of comparison with the basic expression of emotions. The goal of the experiment is to obtain a range of emotions with varying degrees of differentiation and to determine if during the test the emotions will be captured to correspond with the expected results.<br \/>\nExperiment design consists of an initialization dataset, where the stimulus will consist of images, music clips and videos. We will try to create a stimulus scale for this participant and then perform a usability test. Finally, we will use retrospective verbal protocol with each participant to refine the results.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/13_6WoTCVHdeNYtFGf41jyivsM47OpDSVfbGZB44Ux9w\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"gajdosik2018-02\"><em>Eye Tracking Using Deep Neural Networks<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>February 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Patrik Gajdo\u0161\u00edk<\/em><br \/>\n<strong>Supervisor:<\/strong> doc. Ing. Vanda Bene\u0161ov\u00e1, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nEye tracking offers valuable insight in the fields of usability and user experience. However, in order to perform a study where the users\u2019 gaze is being recorded, specialized hardware, eye trackers, are needed, which limits the span of such studies and renders them expensive and time consuming. In order to solve this issue, recent studies focus on using the ordinary web-cameras that are available on most of the today\u2019s mobile devices. Some papers, such as ours, employ convolutional neural networks. The problem is that the variance of images shown to these networks during training is very high and we also cannot easily perform calibration as in the majority of eye tracking solutions. In our work, we focus on exploring the ways in which to alleviate the task for the neural network. We train and evaluate our models on existing datasets as well as on data gathered by proper eye tracker.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1W_ku9x2GC4yIH8rUuovzTGtdnqXQsEA0DW6UVOCjqgA\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<h3 id=\"tunder2018-02\"><em>Analysis of source code reading<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>February 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Mat\u00fa\u0161 Tund\u00e9r<\/em><br \/>\n<strong>Supervisor:<\/strong> Mgr. Jozef Tvaro\u017eek, PhD.<br \/>\n<strong>Short description: <\/strong><br \/>\nThe main aim of this thesis is to determine, how the order of functions in the source code will affect the program comprehension while reading a source code, but also the way of reading itself. In experiments, programmers will read two types of source codes. The first one, where the main function is on the top and the second one, where the main function is on the bottom of the source code. Experiments are taking place in UX lab at the faculty. The effect of the functions\u2019 layout is determined by scanning the information about gaze while reading the source code. To make programmers study the whole source code, there was the task given to them to find errors in the source code.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1G-Sz788VoONQ2sd2x1x_6Uzx3yxed9Sj8bcDks3G8wM\/edit?usp=sharing\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"gaspar2018-01\"><em>Analysis of Influcence of Visual Stimuli on Movies Selection<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>January 2018<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Peter Ga\u0161par<\/em><br \/>\n<strong>Supervisor:<\/strong> prof. M\u00e1ria Bielikov\u00e1, Dr. Michal Kompan<br \/>\n<strong>Short description: <\/strong><br \/>\nIn several domains, items can be represented using not only using the text but also by multimedia, specically images. Images and corresponding visual stimuli may affect user during the web navigational tasks, such as clicking activity in the list of items. In such a list, a user feedback is currently interpreted most commonly from the clicking activity, such that when a user clicks the n-th item in a list, all the previous items are considered not to be relevant for him.<br \/>\nIn our work, we study how visual stimuli can be used in recommendation process. We analyze how visual stimuli should be considered during the analysis of user behavior in the results of recommendations and how the user\u2019s behavior should be properly interpreted if the images are present there.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1VNxka7L9Rc7PrfNs14zvpv6_yMv3u48ctFUpI-hKp_Y\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"hanko2017-11\"><em>The relation of gaze fixations and user\u2019s skill in the digital space<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>November 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>J\u00e1n Hanko<br \/>\n<strong>Supervisor:<\/strong> Ing. Patrik Hlav\u00e1\u010d<br \/>\n<strong>Short description: <\/strong><\/em><br \/>\nToday, the web is a regular part of almost every household. Since not everyone has the same experience with its use, it is important to adapt and facilitate its usability. However, usage depends not only on the experience, but also on the general characteristics of the user. In our case, we focus on his spatial capabilities, that is, as he thinks, perceives and remembers information related to objects and space, from which we derive his spatial cognitive style. This is based on the Spatial Cognitive Style Test (SCST), because we can compare real-space orientation to web navigation, as the web is also considered as a type of space.<br \/>\nOur goal is to explore ways of navigation for users with different cognitive styles. Therefore, we want to identify the differences in the way of navigation, the problems associated with individual ways and to determine to what extent the web navigation is influenced by the spatial cognitive style of the user.<br \/>\n<strong>Link to a formal description of the UX experiment:\u00a0<a href=\"https:\/\/docs.google.com\/document\/d\/1O9RmdZpLlJZ8fdjbg7aSzFWMxXXjy-NwvrdqWjqmj7k\/edit?usp=sharing\">experiment description (In Slovak)<\/a><\/strong><\/p>\n<hr \/>\n<h3 id=\"mokry2017-11\"><em>Identification of the user familiarity with Web domain, based on patterns in eyetracking data<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>November 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Martin Mokr\u00fd<br \/>\n<strong>Supervisor:<\/strong> Ing. R\u00f3bert M\u00f3ro, PhD.<br \/>\n<strong>Short description: <\/strong><\/em><br \/>\nIdentification of repeating patterns from eye tracking data (patterns like sequences of fixations, saccades or areas of interest) is considered to be an important step in eye tracking analysis. Its main focuses are: explanation of recorded interaction, comparison of ways, in which different users interact or clustering of user based on their similarity. This can be used in evaluation of recorded interaction (UX testing) or customization of graphical interface based on identified situation (pattern). This situation e.g. systematic scanning of web page can imply unfamiliarity of user with specific web page. On the other hand, reoccurrences of a similar situation can imply activities of skilled user.<br \/>\nIn our work we focus on automatic identification of patterns in scanpaths in eye tracking data, related to \u00a0level of user\u2019s familiarity. First phase consists of identifying proper features of fixations, saccades, pupils and head distance (features not task-related and with high frequency of occurrences) and analysis of methods for creating common scanpaths and quantification of similarities between scanpaths.<br \/>\nGoal of second phase is to implement machine learning model for automatic identification of user familiarity with e-shop. Model will take as input basic eye-tracking features and will be extended to use also recurrence, reoccurrence metrics and metrics calculated by similarity of scanpaths to common scanpath.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1bkOMBa6B7gG1rl9R8kk8GbewgA65mXNvrI3Pae26zoE\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"redajova2017-11\"><em>Automatic recognition of user characteristics<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>November 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Martina Redajov\u00e1<br \/>\n<strong>Supervisor:<\/strong> Ing. Jakub \u0160imko, PhD.<br \/>\n<strong>Short description: <\/strong><\/em><br \/>\nThis work uses eye movement behavioral scores as a metric for fatigue recognition. We believe that using the method of tracking user\u2019s eye gaze and tracking behavioral scores has a great potential as a method for detecting fatigue.<br \/>\nDuring the verification phase, we plan to focus on refining the results of previous research and performing experiments to verify selected methods, as we discovered several shortcomings in this method. In case of positive results, we plan to design and apply our method in a real life framework for automated learning of user\u2019s fatigue.<br \/>\n<em><strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/19UUzJpFI0f6ASOjhdSck46akGeUsPjlX10AnqHiD3aY\/edit\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"kubanyi2017-11\"><em>The relation of gaze fixations and user\u2019s skill in the digital space<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>November 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Jakub Kubanyi<br \/>\n<strong>Supervisor:<\/strong> Ing. Patrik Hlav\u00e1\u010d<br \/>\n<strong>Short description: <\/strong><\/em><br \/>\nMany information systems use very detailed information about its users for improvement or innovation purposes. Nowadays, statistics of user access and user preferences are used to fulfill these purposes. The other useful information can be user\u2019s skill in the digital space as well. This experiment is focused on analyzing possibilities<br \/>\nof user\u2019s skill determination based on eye-tracker data. When It comes to user\u2019s skill, We have focused on web literacy. The search skill to find, access and evaluate specific information. Research also includes relations in current systems and possibilities of user classification based on their search skills. In this experiment, We have prepared several search-based tasks and we will be examing how participants search for the specific information during the process.<em><br \/>\n<strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1e2E2YFaiK90l-Hwkg9dZW-o2xucnwDUuOuCKYcDkGsI\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"papp2017-11\"><em>Visual attention and saliency mapping on web page elements<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>November 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>D\u00e1niel Papp<br \/>\n<strong>Supervisor:<\/strong> Ing. Jakub \u0160imko, PhD.<br \/>\n<strong>Short description: <\/strong><\/em><br \/>\nIn this experiment, we will use eyetracking for identification respectively for capturing the position of significant elements on the web site.<br \/>\nThe knowledge of salient parts of a web page could offer several benefits for web page designers and users as well. If we know what parts of the web page people use to recognize previously seen pages, we could create compact visual representations of web pages that contain only these most relevant areas.<br \/>\nWeb page designers could also benefit from a model of visual attention to improve page layout and design, e.g., arranging page elements in such a way that users\u2019 attention is focused on the aspects that the author considers most important.<br \/>\n<em><br \/>\n<strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1WhHJlRWtsTm90gT2IyfobPYNsX2A0tBnEkj019zR9Y0\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"sandor2017-11\"><em>Personalized search by using eye tracking to better identifying the user query<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>November 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Filip \u0160andor<br \/>\n<strong>Supervisor:<\/strong> Ing. Eduard Kuric, PhD.<br \/>\n<strong>Short description: <\/strong><\/em><br \/>\nOur goal is to improve the method of calculating user interest.<br \/>\nThis article counts user\u2019s interests based on the number of views per word. This calculation should be expanded by viewing metrics. We believe we will achieve a more accurate representation of user interest by correctly incorporating multiple viewing metrics.<br \/>\nIn the second part of the experiment, we will monitor user behavior when viewing offers and then count on his interest in individual offers. Finally let provide him offer according to his expectations and compare the answer to our calculations and see how much our algorithm is accurate.<em><br \/>\n<strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1CXiN1iDX01_VaG6YdeHrSdXjHa0RHbJi89S2n1Psvgg\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"kostan2017-10\"><em>Facial engagement recognition using sequential analysis<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>October 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Viktor Ko\u0161\u0165an<br \/>\n<strong>Supervisor:<\/strong> doc. Ind. Vanda Bene\u0161ov\u00e1, PhD.<br \/>\n<strong>Short description: <\/strong><\/em>This experiment aims to create a dataset for engagement recognition model. The dataset will consist of videos of participants in three different states \u2013 engagement, mind wandering, disengagement; during text reading and video viewing activities. The project also aims to explore use of sequential analysis in order to distinguish between engagement and mind wandering states.<em><br \/>\n<strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1AKOXrZJuPKge1uj0GJrAw2lKwVQxcDt8QciXLu5hwTU\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"gaspar2017-10\"><em>Eye-tracking of user while reading source codes<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>October 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Mat\u00fa\u0161 G\u00e1sp\u00e1<\/em>r<em><br \/>\n<strong>Supervisor:<\/strong> Martin Kon\u00f4pka<br \/>\n<strong>Short description: <\/strong><\/em>Goal of this experiment is, to set up everything that we need for further testing with eye-tracker on other users while whole semester. We are going to check their eye movements while reading several codes with or without common conventions in them.<em><br \/>\n<strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1DUInCKGzXK7erxvE0MuEMr598S2zIlCz3M73Y8ZHhzU\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h3 id=\"strnadelova2017-10\"><em>Identification of emotions by eyetracking in relation to self-criticism<\/em><\/h3>\n<p><strong>Date:<\/strong> <em>October 2017<\/em><br \/>\n<strong>Experiment conductor:<\/strong> <em>Bronislava Strn\u00e1delov\u00e1 (FSaEV UK)<br \/>\n<strong>Supervisor: <\/strong> doc. Mgr. J\u00falia Kanovsk\u00e1 Halamov\u00e1, PhD (FSaEV UK)<br \/>\n<strong>Short description: <\/strong><\/em>The current pilot study will explore the relationship between self-criticism and face scanning patterns while recognizing photos of primary emotions. Participants will \u00a0complete Forms of Self-Criticising\/ Attacking &amp; Self-Reassuring Scale and a face recognition task while their eye movements will be \u00a0recorded by a Tobii X2 60 eye trackers. Participant\u00b4s eye movements and fixation on faces will be tracked by static images (photos from The Ume\u00e5 University Database of Facial Expressions) of people representing primary-universal emotions (anger, fear, sadness, surprise, joy, disgust, and neutral). There will be 42 photos presented randomly on the screen, as the set includes both men and women in three age groups (about 25 years, 45 years and 65 years). Apart from watching pictures, participants will be asked what emotion on the picture is. The results are important for understanding the role of self-criticism in relation to emotions and their scanning patterns. It can be used for diagnostic purposes and developing as well as evaluation of the interventions for highly self-critical people.<em><br \/>\n<strong>Link to a formal description of the UX experiment:<\/strong> <a href=\"https:\/\/docs.google.com\/document\/d\/1xUEOkGW-V6iMT1xMxqsc1LHxppERSu3kITlxB8_0o7k\/edit#\">experiment description (In Slovak)<\/a><\/em><\/p>\n<hr \/>\n<h4><strong>Archive<\/strong><\/h4>\n<h5><a href=\"http:\/\/www.pewe.sk\/uxi\/spring-2017-2018\/\">Spring 2017-18<\/a><\/h5>\n<h5><a href=\"http:\/\/www.pewe.sk\/uxi\/autumn-2017-2018\/\">Autumn 2017-18<\/a><\/h5>\n<h5><a href=\"https:\/\/www.pewe.sk\/uxi\/spring-2016-2017\/\">Spring 2016-17<\/a><\/h5>\n<h5><a href=\"https:\/\/www.pewe.sk\/uxi\/autumn-2016-2017\/\">Autumn 2016-17<\/a><\/h5>\n<h5><a href=\"https:\/\/www.pewe.sk\/uxi\/experiments-spring-2015-2016\/\">Spring 2015-16<\/a><\/h5>\n<h5 id=\"autumn_201516\"><a href=\"http:\/\/www.pewe.sk\/uxi\/experiments-autumn-2015-16\/\">Autumn 2015-16<\/a><\/h5>\n<h5 id=\"spring_201415\"><a href=\"http:\/\/www.pewe.sk\/uxi\/spring-2014-15\/\">Spring 2014-15<\/a><\/h5>\n","protected":false},"excerpt":{"rendered":"<p>Spring 2019\/2020 Jakub Kubanyi: Analysis of gaze patterns based on user interaction in navigation tasks Marek Otruba: Automatic detection of usability problems Jozef [&hellip;]<\/p>\n","protected":false},"author":10,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/pages\/184"}],"collection":[{"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/comments?post=184"}],"version-history":[{"count":305,"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/pages\/184\/revisions"}],"predecessor-version":[{"id":1825,"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/pages\/184\/revisions\/1825"}],"wp:attachment":[{"href":"http:\/\/www.pewe.sk\/uxi\/wp-json\/wp\/v2\/media?parent=184"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}