- Patrik Brandýs: Impact of usability problems on identifying key objects on the web
- Milan Cák: Identification of Suitable Candidates for User Experience Studies
- Matej Červenka:Analysis of Eye Movement Patterns Depending on Task in the Web Environment
- Mária Dragúnová: Identifying User Characteristics by Eye Tracking Analysis
- Samuel Gedera: Scanpath analysis
- Patrik Hlaváč: Human Behaviour in the Digital Space of the Web
- Michal Hucko: Identification of User Confusion in a Web Application
- Tomáš Juhaniak: Cognitive load evaluation as a part of user studies
- Sandra Kostová: Detecting users’ curiosity
- Jakub Kubanyi: The relation of gaze fixations and user’s skill in the digital space
- Dávid Majerčák: Innovative application within international competition – Webable
- Michal Meluch: Identification of Subjective Complexity and Comprehension Factors of Digital Text
- Martin Mokrý: Identification of the user familiarity with Web domain, based on patterns in eyetracking data
- Daniel Papp: Visual Attention and Saliency Mapping on Web Page Elements
- Filip Šándor: Personalized search by using eye tracking to better identifying the user query
- Adam Talian: Analysis of Source Code Reading
- Matej Valky: User experience improvement based on implicit feedback
- Veronika Včelková:Impact of usability problems on identifying key objects on the web
- Andrej Vitek: Using Probabilistic Models for Analysis of Performed Task based on Eye Movement
- Ján Vnenčák: Scanpath Visualization
Impact of usability problems on identifying key objects on the web
Patrik Brandýs
bachelor study, supervised by Martin Svrček
Abstract: The aim of the bachelor thesis is to find a correlation between problems with usability and identification of key objects. The primary goal is to focus on problems that are associated with poor site navigation, which often causes, that users do not find the key information and they will not visit the site in the future.
The work includes a brief introduction to the problem and compare existing ways to identify usability issues and key objects. We suggest an experiment where the user will have a specific task during which he will be browsing through the site’s specific key objects.
User will also need to identify key objects for a specific task, and successfully interact with them to solve the task. In the bachelor thesis will be comparison of two types of site: with and without navigation problems. Eye tracker will be used to identify these problems more precisely.
Identification of Suitable Candidates for User Experience Studies
Milan Cák
bachelor study, supervised by Eduard Kuric
Abstract: The thesis analyzes the possibilities of identifying suitable candidates for users´ experience studies. It examines existing tools for obtaining and tracking participants for studies. It is primarily focused at selecting right participants of the test, for testing of users´ experience of the website. Nowadays, the users´ experience is a very important indicator of the success of a website for its users. For this reason, it is important that the shortcomings on the website are identified and removed in time. For identifying deficiencies, it is necessary for the website to be tested by the most appropriate participants as possible. Based on input data, it searches and evaluates the group of the most appropriate participants for a particular test of users´ experience. It proposes an experiment and tests its solutions. It also implements new innovative solutions to the system.
Besides that, I’m leading the team of programmers – AMCEF, where we help to present companies themselves with custom web pages.
Analysis of Eye Movement Patterns Depending on Task in the Web Environment
Matej Červenka
master study, supervised by Jozef Tvarožek
Abstract: Users perform various types of tasks on the web every day. Tasks includes searching via search engine, shopping, reading, chatting etc.. It is able to increase efficiency of these processes by recording and evaluating interactions of mouse or keyboard. Except of these devices it also able to use eye tracking technology which allow us to better understanding how users are thinking while performing their tasks. Users are thinking different while performing various types of tasks, which reflect in different gaze plots patterns.
In our research we will try to find and automatically identify patterns in gaze plots which are specific to searching or browsing in e-commerce web applications. On the basis of these patters we want to predict what kind of tasks user was doing.
Identifying User Characteristics by Eye Tracking Analysis
Maria Dragunova
master study, supervised by Jozef Tvarožek
Abstract: Human individuailty is composed of many aspects such as knowledge or cognitive abilities. These aspects have impact on every day life and activies. Using computer applications is not an exception. Eye tracking analysis is a good way of identifying and evaluating some of users’ characteristics and knowing the user is a neccessity if we would like to take into consideration his individuality when we create applications or evaluate usability of a user interface.
We propose to identify individual characteritics of user using appropriate eye tracking measures.
Scanpath analysis
Samuel Gedera
bachelor study, supervised by Róbert Móro
Abstract: Even though devices recording gaze position are not new, it was just recently that the technology became more available and affordable. The data are recorded as a sequence of gaze coordinates that is processed into fixations and saccades. From fixations, it is possible to find out how long a person looked at a certain place. Saccades determine the transition between fixations. Together, they form a scanpath, which makes it possible to determine the sequence, in which the fixations occurred. Recorded scanpaths can be analyzed or compared to each other.
In our work, we focus on scanpath analysis and comparison. The main task is the analysis and implementation of the algorithm for the sequential patterns mining (SPAM), followed by its comparison with other already existing algorithms. The algorithm efficiency comparison will take place on data from an experiment that explored people’s creativity. There are also data from a Big Five questionnaire that participants of this experiment completed. We plan to evaluate similarities and differences in scanpaths between different groups of participants based on their resulting score in the various areas of the questionnaire, such as openness or neuroticism.
Human Behaviour in the Digital Space of the Web
Patrik Hlaváč
doctoral study
Abstract: As we moved to more specific topic, this work should be rather called “Towards Estimating Web Navigation skills from User Interaction”. We are very curious about the different navigation styles (strategies) of skilled and novice users. We selected interesting websites as stimuli and now we are going to test participants with the goal of further explorative analisys. Gaze is one of the investigated features. As part of this process, we design questionnaire suitable for representing user navigation skills.
Identification of User Confusion in a Web Application
Michal Hucko
master study, supervised by Mária Bieliková
Abstract: Confusion 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.
In 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 mouse 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 workin g 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 .
Cognitive load evaluation as a part of user studies
Tomáš Juhaniak
master study, supervised by Mária Bieliková
Abstract: Detection of cognitive load is valuable part of user studies. There are different methods which can detect amount of cognitive load in user studies. In the present, cognitive load detection with use of eyetracking becomes popular.
In our work we propose new method which can detect cognitive load in any web application with only short calibration procedure. Our method focuses on absolute pupil dilation which is proven effect of mental activity. We propose new way how to solve luminosity interference, so we can determine dilation’s size caused by mental activity independent from light’s conditions change. This method allows us measure instant or aggregated cognitive load.
Detecting users’ curiosity
Sandra Kostová
master study, supervised by Jakub Šimko
Abstract: The characteristics of an information system’s user can be very valuable information that can be used in improving the system’s usability and personalization. Depending on the user’s personality, mood or interests, his behavior can be predicted.
The focus of my work is to reveal the users’ curiosity by analyzing their behavior on a web page, concretely on an e-shop website. A questionnaire that determinates the users’ curiosity will be send to e-shop users and according to their answers a classification of two groups will be defined: group of curios and group of uncurious users. Their web activity logs will be in disposal, so these data are going to be analyzed, and from them the best features that could possibly predict the curiosity, would be extracted. A classification implementation method that will predict the users’ curiosity, based on their web activity log is going to be implemented.
The achievement results are going to be verified by using appropriate eye-tracking measures. This would result in possible revelation of the users’ curiosity in real time by using eye tracking data as well.
The relation of gaze fixations and user’s skill in the digital space
Jakub Kubanyi
bachelor study, supervised by Patrik Hlaváč
Abstract: Many 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’s skill in the digital space as well.
In these days, gaze fixations are very popular topic and devices for eye-tracking are more available for masses. My research is focused on analyzing possibilities
of user’s skill determination based on eye-tracker data. When It comes to user’s skill, I have focused on web literacy. To be exact, search skill to find, access and evulate specific information.
Research also includes relations in current systems and possibilities of user classification based on their search skills.
Identification of Subjective Complexity and Comprehension Factors of Digital Text
Michal Melúch
master study, supervised by Róbert Móro
Abstract: Nowadays, people tend to spend considerable amounts of time reading text content on various electronic devices. The amount of perceived text often overwhelms us and we subconsciously use various mechanisms to process it as efficiently as possible. We can observe different kinds of reader behavior that depends either on the personality of the reader or on the characteristics of the text itself. Also, our choice of the reading style is heavily influenced by how interesting, important or comprehensible the given text seems to us.
In our work, we’ll analyze existing ways of determining reader literacy, text complexity and comprehension levels. Using gathered information, we’ll design an improved method for automatically identifying the subjective complexity of digital text. In order to get precise results, our method will rely on eye tracking data, user modeling and structural analysis of the given text. We’ll also evaluate the influence of the reader’s domain knowledge on the subjective complexity and understanding of the processed text. Finally, we’ll inspect some other possible factors such as text readability and its formatting.
Ultimately, the goal of our work is to compare the possible level of impact of all individual factors (mentioned above) on the subjective complexity of the digital text and its overall clarity to the reader.
Identification of the user familiarity with Web domain, based on patterns in eyetracking data
Martin Mokrý
master study, supervised by Róbert Móro
Abstract: Identification 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.
In our work we focus on automatic identification of patterns in scanpaths in eye tracking data, related to level of user’s 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.
Goal 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.
Visual Attention and Saliency Mapping on Web Page Elements
Daniel Papp
master study, supervised by Jakub Šimko
Abstract: Nowadays websites are part of everyday life and people want to use them intuitively. Therefore site owners invest a lot of money on design and usability in order to get the most users. Currently usability testing usually is done in laboratories of user experience. During the interaction with web sites, data is collected (such as video record of screen or face of the user, clicks and mouse movements and oculography data). Evaluation of the results of such a study is difficult. Experts evaluate the collected data manually. For the purpose of reducing the effort of experts would be good to automate these evaluations as much as possible.
In our work, we focus on the automated identification of salient DOM elements, areas of interest and user-friendliness (detect the correct deployment of DOM elements, detect F-model) website. Solution has to be verified in the laboratory user experience and interaction of the faculty.
Personalized search by using eye tracking to better identifying the user query
Filip Šándor
master study, supervised by Eduard Kuric
Abstract: This work is aimed at automatically creating a user’s interest model on the domain of the Internet shops. In particular, it will be the discount portal ZlavaDna.sk, and the internet shop Alza.sk. This site contains products and their description. When the user looks through the products, our method will create a user interest model and thus reveal the user’s interest. In process of creating a model, we use data from a view that tells us what and how the user has been tracking, and accordingly we calculate its relationship to that term.
User tracking allows us to create a model of interest that reflects user interest more accurately with viewing technology. We’re focusing on enriching your current interest tracking of eye tracking metrics. Subsequently, we will try to predict his interest in the product from the collected user view information. We verify the correctness of the model by a suitable experiment in the user experience laboratory at our faculty.
Analysis of Source Code Reading
Adam Talian
bachelor study, supervised by Jozef Tvarožek
Abstract: Difficulty of source code reading is different for programmers with various skills. Programmers – experts have their own habits how to read a code which makes algorithm friendlier for them. These habits are probably very similar. But novices don’t have these habits. Their methods of source code reading are more random. And this is what is interesting for me. In my research I’ll try to find some patterns in their thinking and understanding of the code. For this purpose, I am planning to use eye-tracker and record their eye gaze while they solve short tasks written in C programming language. These tasks will consist of short source codes (up to 30 lines) and the participant should read and comprehend it and specify the output of the program’s execution. I should be able to collect enough data for analyze and hopefully I’ll be able to find some pattern in their scan-paths.
User experience improvement based on implicit feedback
Matej Valky
master study, supervised by Mária Bieliková
Abstract: Critical factor for an application success is an intuitive user interface. We live in time of constant change as new applications or new functionality of existing ones are created. The user has to often adapt for this alternation. Applications often offer a tutorial tool, which helps the user and guides him through a task step by step. In spite of user friendly interfaces, guides and tutorials, the user can find himself in undesirable affects, as he does not know how to progress next, he is frustrated or confused.
The identification of those affects and proper reaction is challenging issue, which is swayed not only by application design, but also by his level of proficiency and his actual intent, which we do not know. By interception of those situations, their identification and appropriate reaction we should essentialy improve a product’s usability.
In this work, we focus on intrusionless tracking of user’s implicit and explicit feedback. We aim to make model of confusion and related affects. We would like to refine guide and tutorials.
Impact of usability problems on identifying key objects on the web
Veronika Včelková
bachelor study, supervised by Martin Svrček
Abstract: Eye tracking, mainly in the context of usability testing (a testing designed to analyze the usability of a web from the perspective of a user) is increasingly more studied and developed technique nowadays. Some reaseach papers even prove that usage of an eye tracker is superior to survey based testing when it comes to the accurancy of conducted measurements.
In this thesis we focus on analyzing the impact of selected usability problems (problems related to the web that are generally disliked by users) on the ability of a user to identifying a key object related to certain task on the web. A key object in this context refers to an element of a web page which is essential to be noticed or even used by the user to finish a given task. To fufill the goal of this thesis an experiment on multiple participants will be conducted. Analysis of the experiment will be done using data provided by an eye tracker. Desired outcome of the analysis is concluding which usability problem affect user the most. Results could provide useful guidlines to follow during designing a new web or administrating an old one.
Using Probabilistic Models for Analysis of Performed Task based on Eye Movement
Andrej Vitek
master study, supervised by Jozef Tvarožek
Abstract: Usage of dynamic web applications to solve office or personal tasks has become part of our everyday life. Way how people look, while solving these tasks, reflects not only what task are they solving, but also their level in given domain or personal characteristics. Scanpath is formed by fixations and saccades in time and models, which use only statistical informations about scanpaths are losing important information. Probabilistic methods present a new way, how to model eye movement as time-series information and can efficiently capture stochastic character of scanpath. In this work I am using probabilistic models like Hidden Markov Model or Gaussian models to create features and model eye movement data. Based on used data and selected domain, I will be predicting task at hand or user characteristics.
Scanpath Visualization
Ján Vnenčák
bachelor study, supervised by Róbert Móro
Abstract: We 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.
In our work, we analyzed existing methods of visualization of eye tracking data. We aim to find ones that are capable of supporting specific visualization tasks in a better way then methods already implemented in commercial eye tracking software. We plan to implement the selected methods and compare it with the existing ones (such as gaze plot or heat maps) in a user study.