Students’ Research Works – Spring 2016: User Experience and Implicit Feedback subgroup (PeWe.UX)

User Experience on the Web

Veronika Balážová
bachelor study, supervised by Róbert Móro

Abstract. Nowadays, when almost everything can be found on the Web, it is important for the websites to be as usable, user-friendly and easily searchable for what the users need as possible. In addition, it is now true more than anytime before that “competition is just by one click far away from us”. That means if a website does not give the users exactly what they need, they leave the page and look for the information somewhere else, or this experience make them dissatisfied, angry, or frustrated.

A user interface of a website determines how the users will use the site – whether they will effectively reach their goals, less effectively, or not at all. Therefore, it is important to improve user experience of a website in order to find information in the most effective way. This may be also related to the fact, what kind of person the user is.

In our work we focus on user experience on the Web related the banking domain, especially on the navigation. We conducted a formative study in order to test usability of a website and its navigation. At the present, we have already identified usability issues in the interface and we have offered improvements, which was the main goal in formative study. During the usability testing, we have also collected information about personality of each participant, since this information was useful in the evaluation, especially when interpreting the results. Now we plan to implement our recommendations and test the website again and compare results with the original. This will be realised by the summative study. We expect, that there will be higher success rates and lower time in solving the tasks.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 73-74 –>

Search engine keyword prediction based on user need derived from eye tracking

Jozef Balún
bachelor study, supervised by Eduard Kuric

Abstract. Today there is a rule which says: It is not necessary to know everything, you just need to know how a where to find it. It only confirms that it is a key human ability to search for good information.

In this project we introduce an improvement to phrase prediction used in search engines. Suggesting phrases is an important role in using search tools. Many researches were focused on improvement of query estimation based on mouse movement and clicking, scrolling and time spent reading the document. However, our method should ensure improvement by predicting queries right away from actuals user’s view so the user could get queries in real time. User’s view can be tracked by a device called Eye tracker, which returns information about eye fixation in real time. Based on the collected information we can predict user’s intention by our method and suggest queries which result from the context of user’s read material. Queries can by used directly as a suggestion for the next searching of the user in the context of his relation.

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Measuring Working Memory Capacity through the Use of Game Pexeso

Zuzana Beníčková
bachelor study, supervised by Jozef Tvarožek

Abstract. Working memory plays an important role in our cognitive functions. The higher capacity of memory we have, the more information we are able to absorb in one time. For these reasons, the capacity of the working memory is an important factor in many fields such as evaluation of respondents in experiments as well as when dealing with students in teaching.

In this study, we aim to find new way of measuring working memory by using a modified memory game Pexeso with mathematical problems as pairs to look for. In evaluation, experiments are designed to compare subjects’ performance in game Pexeso with their performance in established measures of working memory. Also, we examine patterns in playing Pexeso based on WM capacity. We will conduct an extensive study in which we collect data on several game sessions, which major part will take place at OntoParty, 19th PeWe session.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 75-76 –>

Mind-controlled application

Patrik Berger
bachelor study, supervised by Róbert Móro

Abstract. The computers have become a part of our everyday life, interaction with them is carried out mainly through the well-known ways that are mouse and keyboard. Recent progress in BCIs (brain-computer interfaces) offers an alternative. Most of the BCI systems nowadays use EEG devices to acquire the brain signal. Those EEG devices are usually much simpler than the ones used for medical purposes, use smaller amount of electrodes, are portable and quite affordable. Examples of those low-cost EEGs are Emotiv Epoc or NeuroSky.

In our work, we propose an EEG signal processing method in order to recognize P300. It includes selecting channels (electrodes), filtering the signal to get rid of the noise and final classification of the processed signal. We mainly focus on the channel selection part, where we propose a genetic algorithm (GA) combined with the linear discriminant analysis (LDA) to select the best subset of the channels. We want to find out whether our method will be effective enough to recognize P300 even with a low-cost EEG device like Emotiv Epoc and if so, what accuracy we can get. We also want to compare our GA-based channel selection method with using all channels and with using the recursive channel elimination method, which should be able to find to the best subset (and, therefore, will be used as our baseline). We hypothesize that accuracy while using our channel selection method will be significantly better than using all channels and slightly worse but faster than recursive approach. We also assume that our method should be able to recognize P300 from the Epoc data.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 77-78 –>

Utilization of games as educational means

Peter Bobovský
bachelor study, supervised by Jozef Tvarožek

Abstract. Gamification has been used to stimulate motivation in students for a while now. Using gamification as an introduction to programming and algorithmization is an important step in teaching the subjects. In this project I study which specific elements tied to gamification will keep the students engaged and drive them to complete more problems.

My goal is to distinguish which elements boost the student’s motivation and which detriment it. These elements can range from simple rewards, time limits to scoring and social elements.

These findings will prove to be useful for uses in projects focused on teaching programming or other teaching sectors which use gamification.

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Pupil Dilatation and Stress in User Studies

Matej Červenka
bachelor study, supervised by Martin Krupa

Abstract. Analysis of user testing records consumes much of the study moderator’s time. If we want to find a problem in user interface, it’s necessary to watch whole record of the testing and focus on all its outputs.
Forms are one of the most problematic features of the user interface. We assume that problematic forms cause stress, cognitive overload and negative emotion of users. These phenomena are manifested by mydriasis (pupil dilation), which we are able to measure with eye tracker. Our primary metric is pupil size. Alternatively we will monitor emotions (Nodulus Face Reader) and skin conductance (GSR).

If we find a correlation between mydriasis and stress that was caused by problematic areas of forms, we will be able to determine time at which the participant had a problem. The goal is to develop a tool which determines times of problematic areas and saves moderator’s time which he would spend on finding these areas.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 79-80 –>

Evaluation of User Experience by Eyetracking and Emotions Analysis

Mária Dragúňová
bachelor study, supervised by Mária Bieliková

Abstract. Measuring of the web page target findability is often used to evaluate web page designs usability. Eye tracking provides us several measures, such as time or number of fixations prior to the first fixation on the target. However, people are different and therefore the measured values differ. Our work is based on the natural diversity of human visual search abilities, since visual search is subject of attraction for many psychologists around the world. We evaluate the participants’ visual search ability not only employing the standard visual search tests, but also by our developed tests, which contain typical icons from the web environment. This set of tests will be created according to the results of an quantitative experiment, choosing the stimuli with significant variety of response times of individuals.

We evaluate our solution by computing correlation between our evaluation of visual search ability and the number of fixations prior to selecting the target element in a search task on chosen web page. If the correlation is proved, we will be able to enhance target findability measure by assigning a weight to each participant in a user study according to his visual search ability. If his visual search ability is poor, participant will be expected to reach worse results in search tasks and therefore his worse result does not necessarily indicate a problem in user interface, but only a poor human ability.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 81-82 –>

Towards Automating Analysis of Eye Tracking User Studies

Peter Dubec
master study, supervised by Mária Bieliková

Abstract. Usability is a quality attribute that assesses how easy user interfaces are to use. The word “usability” also refers to the methods for improving ease-of-use during the design process. The traditional usability testing demands testing in specialized usability laboratories and in many cases it requires test moderator or commenting work by the participant. Main goal of our work is to automate analysis of eye tracking studies, however we are specifically focusing on usability testing of mobile applications.

Nowadays usability testing of mobile applications with use of eye-tracking is realized as traditional usability testing. Therefore it requires specialized laboratory and test moderator. Also it is not possible to perform mobile usability testing on multiple participants simultaneously, therefore in most cases these tests are qualitative and not quantitative because we are able to collect only small amount of data. Our main goal is to make bulk testing of mobile applications possible by means of simulating mobile applications on PC and collecting data from PC. Interaction with PC is quite different than interaction with smartphone, but we believe that there are certain usability problems which we will be able to identify also during emulation on PC and also we will be able to collect more precise data from eye-tracking thanks to bigger displaying screen. Later thanks to better quality of collected data, we will be able to perform automatic analysis of these data and automatically evaluate specified usability metrics.
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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 83-84 –>

Impact of Characteristics of Individuals on Evaluating the Quantitative Studies

Patrik Hlaváč
doctoral study, supervised by Mária Bieliková

Abstract. The current state of informatization of the world and the presence of information technology in almost every area of our life requires efforts of users to adapt to different environments – system interfaces. Ability to work with such an environment depends on the time and duration of the interaction, functionality and also from information architecture. This also includes differences in information behavior of users (it is very individual and depending on the experience, knowledge, goals, locations and social contexts differs). We focus on the evaluation of user sessions, mainly on individual participant differences in the quantitative study.

Recent usability studies in a web domain are based on different metrics, but the question is how to apply these metrics to evaluate a larger group of people. When we consider that every user has different qualities, skills and experiences, we could expect that the results of testing will get different values. We assume that quantitative studies will provide more accurate results with information enriched with personality traits.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 85-86 –>

Analysis of User Activities in Web Browser

Mário Hunka
bachelor study, supervised by Martin Labaj

Abstract. Web browsers are todays access points via users browse the Web content. There are many functionalities that are offered to the user. The thing that we are concern about is parallel browsing. Since it was added to web browsers, it changed the way we browse the Web. Many actions can be accomplished by different ways. There are many questions that can be asked – where are the user looking at? How does he switch between tabs? Does he use tabs more than multiple windows?

There are many studies, which have been interested in tabbed browsing. Furthermore, we have datasets from our faculty available, which can be used as well. We analyze this studies and datasets to find out their results and inspire ourselves to make our own experiment. In our thesis, we aim to implement and realize experiment in UX lab with a certain group of people who will perform a special task.

Eventually, we try to propose analysis of this work, which should lead to better understanding of behavior of parallel browsing. It can be achieved by interview the respondents that can support and clarify results from data or by comparing those results with one that already exits and finding the similarities and differences. From the conclusions we should be able to suggest some relevant improvements of future web browsers.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 87-88 –>

Analysis of User Activities in Web Browser

Miroslav Hurajt
bachelor study, supervised by Martin Labaj

Abstract. Web as a recurrent activity shows that a key aspect of the use of web browsers are revisitating mechanisms and page revisitation associated with them. In our thesis, we try to offer an analysis of the work of a group of users by monitoring perspective and areas of interests on the web sites and parts of a web browser. Further, we realize an experiment of analyzing ordinary work while using the web browser by a group of participants representing a programming user group. We have proposed a method to simulate ordinary work in a web browser by this group of users. The experiment will offer a detail view of a closer analysis of behavior in the short-term page revisitation and usage of revisitating mechanisms.

The main goal of this thesis is to perform quality analysis leading to possible implementation improvements or basis for better understanding of the user behavior representing a programming group of users in web browser.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 89-90 –>

Search query expansion based on user’s intent derived from eye tracking

Patrik Januška
bachelor study, supervised by Eduard Kuric

Abstract. Internet has become an integral part of everyday human life. Millions of users interact with various search engines on a daily basis. Man as a user searches internet Web pages for required information. Queries, characterizing wanted information, are entered into browser interface by users. Search engine then returns list of relevant pages, based on its own database, containing wanted information. Users visit these pages, spend some time on them, click on ads, modify queries and perform other actions. Query represents key part of information retrieval. In this context, query is defined as word or group of words describing or characterizing retrieved information. Biggest problem we face is creation of said query, whose execution results in relevant information and thus retrieval success. Main goal of browser is to provide user with the most relevant information from query result. However, user doesn’t always find resulting information relevant.

Recently, a wide variety of studies on information retrieval (IR) have focused on tracking users’ eye movements, and the use of high-performance cameras or eye-trackers has made application of this technique much easier than before. The method we propose in this work can be regarded as a type of implicit relevance feedback because it estimates a user’s search intent implicitly from data about where the user looked while browsing Web pages.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 91-92 –>

Robust Detection of User’s Cognitive Load Using Personalized Pupillary Response Model

Tomáš Juhaniak
bachelor study, supervised by Mária Bieliková

Abstract.Information about cognitive load of a user can be very useful for appropriate system adaptation and personalization, especially if they can be measured in real time. As was shown by previous research, human cognitive load is reflected by pupillary response, measurable by eye-tracking devices. However, practical exploitation of this phenomenon (e.g. in adaptive systems or user studies) has been limited due to other factors that influence pupillary dilatation, namely changing luminosity of device screen. In our work, we develop a pupillary response data washout method that reliably filters-out the luminosity noise caused by changing screen content. We want to demonstrate this method in a controlled, eye-tracking study as part of OntoParty, 19th PeWe Ontožúr.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 93-94 –>

Game-based support of online learning of programming

Peter Kiš
master study, supervised by Jozef Tvarožek

Abstract. Lack of motivation of students is one of the main barriers to efficient learning. In the case of online learning there are also suppressed natural human and social aspects, so the lack of motivation causes even worse results. Therefore, research is still looking for new ways to increase students’ motivation for learning online. Games and gaming principles improve entertainment and increase overall involvement of students. Both of them are increasingly used in the online environment. Use of games and game principles, graphical visualization, and entertainment content for teaching programming opens the way to explore the impact of these elements in the learning process, the speed of acquiring new knowledge and the ability to select the most appropriate procedures for solving algorithmic problems.

Considering the typical source code writing exercises are already well implemented in teaching programming, we decided that in our work we will focus on creating novel types of programming exercises through the use of existing codes that students produced over the past years. For new students, we want to prepare a diverse range of tasks from these codes, aimed on the understanding, analysis and description of the code, the code refactoring and use of best practices in programming.

In our work, we propose a diverse range of tasks generated from existing codes, aimed on the understanding the code and on using of best practices in programming. Innovative tasks would be part of competitive environment, where students should compete each other in speed, accuracy and knowledge. Actually we prepare experiment in which student will solve prepared tasks from which we want to collect metrics of their interaction and evolution of motivation.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 95-96 –>

Automatic Estimation of Developer’s Expertise

Eduard Kuric
doctoral study, supervised by Mária Bieliková

Abstract. Expert recommendation systems in software engineering help to locate (discover) and to recommend individuals (experts) who have appropriate expertise on a given source code artifact. Estimation of developer’s expertise can be a valuable asset for a software company. It can be beneficial in the planning of a software project, especially in assigning development tasks. The time required to implement a new functionality, to change an existing functionality, or to fix a bug can be significantly reduced if the (issue) task is assigned to a developer who knows corresponding source code.

Developer’s expertise can be defined as a degree of his/her familiarity with a software system (software project), respective to other developers of the system. Existing approaches to estimate developer’s expertise on a part of a software system rely on the assumption that a number of lines of code committed by a developer reflects his/her expertise on that part of the system. However, we believe that in addition to the amount of final code we should also consider how much effort he/she put into implementation of the code.

In our work we propose an automatic approach to identify and to recommend an expert for a given development task of a software project that considers both a degree of developer’s familiarity with the task and its corresponding source code, and his/her development productivity. A software system can be viewed as a body of knowledge decomposed into a set of fragments called conceptual concerns (topics). We estimate developer’s familiarity with the software system at level of topics. We build a topic model to extract topics from codebase of the system. A degree of developer’s familiarity with a topic is estimated from his/her code contributions to source code of the topic. We estimate developer’s productivity as complexity (size) of code changes performed by the developer per time and the amount of effort he/she spent to perform the changes measured through his/her development activities.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 97-98 –>

Automatic Evaluating Usability of Applications with Eye-tracking Technique

Lenka Kutlíková
master study, supervised by Jakub Šimko

Abstract. Nowadays working with computers is part of our lives. Every day we check new emails, read the news or find useful information for school or work. We visit the big amount of websites with different purpose. Some of them are better than the others. We can assess how good the website is by testing usability. Usability is defined as the ease of use for people. Researches with developers try to improve usability of websites. Nowadays they use eye-tracking technique for testing them.

Our experiment is focused on reading instructions. In experiments and also in real life people usually do not read instructions. Even if there is an manual for product, game rules or instructions for filling questionnaire or doing an experiment people firstly try to do it on their own without reading instructions. They go back to them only if they do not know what to do. The goal of our research is to find if people read instructions. We suppose that eye-tracking metrics indicate that users read them. We conduct an experiment consisted of four tasks. For each task we can find if participants read instructions or not. We plan to use eye-tracking technique. Tracking of eye movements products a big amount of data. We plan to find automatic way how to analyze them.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 99-100 –>

Gathering Tabbed Browsing Behaviour as User Feedback on the Adaptive Web

Martin Labaj
doctoral study, supervised by Mária Bieliková

Abstract. Everyday activity on the Web includes everything from grocery shopping, education, employment, communication, learning, to entertainment. Web systems that support such aspects of human activities are becoming more adaptive than before. A web system first needs to know the individual users through their actions in order to facilitate any adaptation. In our work, we focus on observing, logging, analysing and utilizing both implicit and explicit user feedback. Apart from explicit feedback questions presented to the user at the appropriate moments for obtaining better and more extensive explicit evaluations, one particular area of our research lies in observing user’s movement across web pages – the parallel browsing.

Before we can even analyse and model the parallel browsing behaviour and use it for user modelling, improving domain models, or recommending resources to users, we need to capture it. In one approach, using a tracking script, we can easily observe every user of our application without user’s additional steps, but only the visits to and switches between pages from a limited set are observed. We used this approach to recommend learning objects relevant to exercises solved in a learning system.

In another approach, when we observe the user’s browser, for example through an extension, we see user’s every step across various web applications, even when the user leaves our application to look for additional information in other web systems, but we only see actions of a limited user group who choose to participate. We previously used this approach for automatically enriching learning content with external resources.

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Evaluating the Usability of Applications Using Gaze Tracking

Vladimír Ľalík
master study, supervised by Jakub Šimko

Abstract. At the present time success of software depends not only from functional aspects, but also very important is experience which application provides to users, while they effectively and efficiently achieve specified goals. Therefore usability evaluation is important part of software development. When we need determine level of usability in an application, the best way is to let users interacting with application, while we watch their behavior, asking a questions, record their activity.

Usability testing with users is time and money consuming, therefore our effort is to obtain as much information as possible from users. Now we can use gaze-tracking to obtain more information on how the users ponder while they interact with application. These data can provide a different perspective on what attract the attention of the users or where they were trying to find information. We can obtain a big set of data from gaze-tracking, but an analysis of these data is extremely time consuming, because this process is not sufficiently automated.

Our goal is to design method which will automate process of evaluation interfaces with the data obtained from eye tracker during usability testing. We analyzed recent studies which provides us metrics and patterns in gaze-tracking data determining specific usability problems. We conducted experiment in which we validated some of patterns identified in literature. On the grounds of this metrics and patterns we designed method which automatically analyze and identify usability problems of web interfaces in gaze-tracking data from usability testing.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 101-102 –>

Mind-Controlled Application

Tomáš Matlovič
bachelor study, supervised by Róbert Móro

Abstract. With successful classification of emotions we could get instant feedback from users and increase the potential of affective computing.
In our approach, we aim to evaluate EEG device Emotiv EPOC and classify emotions from the data captured by this device. We proposed a method of emotion classification, which we evaluated on an existing dataset. The preliminary results show 37.72% accuracy of our approach. In addition, we conducted an experiment, in which participants watched music videos. We used EPOC to capture the electrical signal from their brains. In order to verify the potential of the EPOC Emotiv device for classification of the emotions, we plan to compare it with one of the existing tools, namely Noldus FaceReader.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 103-104 –>

Human-based Computation with the Use of Gaze Tracking

Aleš Mäsiar
master study, supervised by Jakub Šimko

Abstract. Effective processing of large amounts of information is considered to be one of the problems of current information systems. To some extent, it is possible to automate the process, but often the acquired knowledge is not sufficient for required needs. In those cases, it is common to use a human-provided input, which helps to extend the existing set of knowledge. One of the ways is to use experts to provide information, which is generally of high quality and also is considered to be correct, however, the amount of acquired information is vastly limited. Commonly used alternative is knowledge acquired from large crowds of people, that provide large amounts of data, but without the guarantee of its correctness. This approach can be considered as human computation.

Many human computation approaches struggle with the problem of correctness validation when processing individual answers. Several methods exist, that deal with this problem, but lot of them cannot be applied until there is sufficient amount of answers for the evaluated task.

This work focuses on creating a method, that deals with the problem of correctness evaluation of individual’s answers in a human computation task and for that it uses information acquired from gaze tracking device. This work also addresses application of the designed method on specific tasks and its integration to the task providing system for the purpose of more effective use of crowds’ work.

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Universal tool to assign badges in online communities

Martina Redajová
bachelor study, supervised by Ivan Srba

Abstract. The application of gamification is becoming a widely used technique of an activity motivation not only in learning process in educational domains, but also in other domains with no such purpose. The main goal of various gamification mechanics is to motivate users to visit a system, be active in this system and to have another reason to come back regularly.

There are many types of game elements used to achieved this, such as leaderboards, storytelling, achievements and application of levels or badges. Assigning badges is one of the most promising elements of gamification because it is rewarding users for their activity with no need of permanent focus on progress. It is proven that user’s ambition to earn a badge is provided by natural human desire of owning something. However, choosing right activities to be rewarded for and correct definitions of activity boundaries to assign badges, seems to be often a problem for web domains creators and there is just a few tools developed to solve this problem.

In our work, we are going to create a front-end for a universal tool for assigning badges focusing on creating correct rules for assigning badges and creating design of these badges. Correct choice of activities users should be rewarded for and correct definition of boundaries for assigning certain badges will be supported by specifically proposed visualization of users’ activities, which will be provided by our tool.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 105-106 –>

Explicit User Input Quality Determination Based on Implicit User Input

Metod Rybár
master study, supervised by Mária Bieliková

Abstract. Implicit feedback can provide us with information that we can use to help us evaluate online questionnaires. Using this information, we could eliminate number of necessary explicit feedback and we can better evaluate the results. This would allow us to simplify the questionnaires and also improve the result quality. Explicit information from the user may be incomplete or misleading. This is currently being dealt with using complicated questionnaires and forms asking the same question multiple times differently, to avoid getting misleading information.

Using implicit measures as pupil dilation or eye-tracking we have created first model for deception detection in environment of online questionnaires. We are currently working on verifying of our first results and creation of new metrics, that can be used to improve our model, based on galvanic skin response or EKG.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 107-108 –>

Automated evaluation of website usability in terms of user experience

Matej Schwartz
bachelor study, supervised by Eduard Kuric

Abstract. With the evolution of Internet and its use in everyday life we ​​come into contact with websites in increasing numbers. Searching for information, communicating with loved ones or business is the reason that we use web every day. From the educational objectives to grocery shopping online. When searching or using services provided on Web we need to verify whether the websites is functional and simple from the user point of view. When websites fail to comply with certain habits, it may discourage user and reduce its visit rate.

Website usability testing is mostly done manually, by group of testers, which focus on design errors. Testers are ordinary users who try to perform the given task. During execution they face problems which could lead towards discouraging real users from accomplishing tasks. This form of testing is very time consuming and demanding on human resources. By using the modern technology, we come to automated evaluation of website usability.

Websites are used by people in different countries, in different age ranges or by people with disabilities. While interacting with Websites, disability is often represented blind people or otherwise visually impaired. Our goal is to automate evaluation of the usability of web site from the perspective of people with impaired recognition of the colors and then change the interface so that it can be used. The aim is to give users with this type of disease an ability to use services as well as users with no disability.

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Analysis of Reading Difficulty in Web Environment

Martin Štrbák
master study, supervised by Marián Šimko

Abstract. Success of Web applications depends on their ability to recognize user characteristics (interests, knowledge, type of personality etc.) and apply them to improve offered services. Mostly, these characteristics are acquired trough analysis of interaction of user with concrete Web application (where is clicking or looking, what is writing). More difficult is to determine if textual web content is interesting. One method to identify if reader is satisfied with content of document is to ask him. This approach has its limitations, because people are not always very honest, or have their own perception of classifying things as boring or entertaining. Questionnaire is a bit more objective. Most used technology nowadays is eye-tracker, which monitors human gaze during process of reading. Another methodology might be to analyze brain waves of user with electroencephalograph (EEG) while reading and compare them when his neural activity is idle. We will use this to determine whether text is difficult or easy to understand for human reader.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 109-110 –>

Automatic Segmentation of a Screen Recording for Scene Identification

Jakub Benjamín Vrba
master study, supervised by Jakub Šimko

Abstract. Users are daily interacting with several application or websites, during their work with computer. User experience is a term, that describes
how users subjectively perceive those systems.

Traditional method of testing applications demands user to be spectated and his behavior is evaluated by researcher manually. This approach may be applicable only with small number of participants – qualitative research. For quantitative test, in which tens of users participate, would be this type of evaluation challenging. In consequence it is needed to gather data about user interaction from eye or mouse trackers and evaluate them afterwards.

In a phase before analysis, it is neccessary to identify scenes. Scene represents time segment of a screen recording video, during which the examined application remains on a single screen, in order to map data from trackers and apply aggregation metrics. At the present time scenes are annotated manually, that means researcher must go through every recording. Purpose of this thesis is automatic segmentation of a screen recording for scene identification, for the sake of making this process faster and easier. Image processing is ideal technique for implementing this automation.

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<!– | In Proc. of Spring 2016 PeWe Workshop, pp. 111-112 –>