Attention Deficit Hyperactivity Disorder (ADHD) presents specific cognitive and attentional characteristics that can significantly affect web navigation and information processing. Despite the widespread adoption of the Web Content Accessibility Guidelines (WCAG), there is limited empirical evidence addressing their effectiveness for users with ADHD. This study evaluates the applicability of accessibility and usability guidelines through a set of controlled user tests conducted with adolescents diagnosed with combined ADHD. The tests assess multiple web design elements, including multimedia presentation, sound control, content layout, textual clarity, temporal elements, links, and iconography. These tests were adapted from previously validated experiments conducted with other neurodiverse users. Quantitative results were obtained by measuring task completion times, complemented by qualitative observations of user behavior. The findings reveal that certain guidelines significantly improve performance for users with ADHD, while others produce results that differ from standard WCAG recommendations. The results highlight the importance of considering the specific cognitive profile of users with ADHD and avoiding generalized accessibility assumptions. This study provides evidence-based design recommendations to support the development of more effective and inclusive web interfaces for this user group.

The ability of robots to detailed navigate and map environments is crucial for many industrial tasks. Traditional robotic control methods, using frameworks like ROS2 (Robot Operating System) combined with tools like SLAM (Simultaneous Localization and Mapping) and NAV2 (Navigation 2), often require specialized programming knowledge, limiting accessibility for non-expert users. Recent advancements in Large Language Models (LLMs), could offer a promising alternative, enabling robots to be controlled through natural language commands. These LLM-driven systems have the potential to simplify robot interaction by translating high-level language prompts into detailed movement, mapping, and exploration tasks. There is a lack of existing solutions for utilizing natural language commands in certain movement and trajectory tasks, particularly in exploration scenarios. Current approaches are not equipped to effectively translate contextual references (e.g. next to the corner, between doors, towards the nearest unexplored area, etc.) into concrete robot commands. This proposal integrates LLMs with ROS2, SLAM, and NAV2, allowing users to issue natural language commands for detailed navigation, path planning, and mapping tasks including unexplored areas. By reducing the technical barrier to robot control, our system enables more intuitive and flexible human–robot interaction in complex environments, making robotic systems accessible to a broader range of users. In the explored scenarios, the proposed approach successfully transforms most of the users’ textual prompts into a set of robot commands, achieving an F1-score of 0.913 for the successful transformation of entire prompts (composed of multiple sub-prompts) and an F1-score of 0.975 for individual commands.

Students’ motivation is one of the factors that directly affect academic performance. In recent years, teachers are looking for ways to motivate students during their training period. For example, making use of slides, videos, films, comics or games to increase students' motivation to improve their learning experience. Some research works have revealed that multiplayer games which include cooperation and competition, among other factors, are an extraordinary tool for enhancing students’ motivation. Current alternatives make it very complex for teachers to create multiplayer games for their students. The definition of the game requires many configurations and even technical knowledge. This research proposes a new platform that allows teachers to create multiplayer video games in a simple and fast way, improving the game creation process over current alternatives. The resulting games are also designed for to improve the student experience, and make it fun. These games do not only include trivia questions, but also use functional mechanisms from video games. The design of the generated games allows students to master the games in a short period of time during their classes.

Automated keyword extraction is widely used for tasks like classification and summarization, but generic methods often fail to address domain-specific requirements. In education, texts are designed to help students grasp and retain key concepts needed for exercises and resolve questions. Despite the variety of existing keyword extraction algorithms, none are specifically adapted to the unique structure and purpose of educational materials like textbooks or lecture notes.Supervised methods have demonstrated their effectiveness in various domains through advanced techniques like contextual embeddings and domain-specific fine-tuning, Our study proposes a novel solution leveraging pretrained transformer models, specifically BERT, to adapt to the structure of educational materials for effective keyword extraction. Our research demonstrates that by fine-tuning BERT models to the specific characteristics of educational texts, we can achieve more accurate and relevant keyword extraction. YodkW, our adapted model, outperforms traditional algorithms in identifying the key concepts that are essential for educational purposes. Performance is quantified using the F1 score relative to text books key terms list, Preliminary results demonstrate that our approach can improve the identification of key concepts pertinent to student understanding and facilitate the automatic generation of test questions.

User experience is a crucial aspect of software quality, and while various guidelines and heuristics have been proposed to enhance it, tables have not received as much attention as other elements. Additionally, many developers are unaware of the guidelines they should follow in this regard. The objective of this article is to enhance the user experience on websites by streamlining the development process of usable tables. To achieve this, we propose a set of heuristics integrated into a tool called BetterTable that enables automatic application of usability improvements while parsing the HTML document. The complexity involved in developing a table with applied usability guidelines is evaluated using different implementations: the proposed approach, DataTables, and AntDesign. Furthermore, tests are conducted to validate the effectiveness of the proposed heuristics through user interactions with 13 table usage scenarios, measuring time, mouse movement, and clicks. Each user is randomly presented with 13 scenarios that either meet or do not meet a specific guideline. The results indicate that our proposal reduces implementation complexity by 43.83% and 24.69% compared to DataTables and AntDesign, respectively. Moreover, user testing reveals that 6 out of the 13 guidelines show improvements in at least 2 of the 3 calculated metrics. Guidelines fulfilled show 40.37% less average completion time and 20.39% less mouse movement than the baseline. Based on the conducted studies, we observed that compliant tables, on average, exhibit reduced user time and mouse movements compared to non-compliant tables. However, no significant differences are found in terms of clicks.

In recent years, Internet of Things (IoT) systems have changed the way we live, work and do businesses in many areas, even those that until recently seemed unlikely. Some areas that can benefit from their application are, among others, healthcare, smart cities, industrial automation, smart agriculture, intelligent transportation systems, smart logistics, and emergency response. This research work proposes a novel alternative that allows the creation of IoT systems capable of making remote changes in devices' communication in a fast and agile manner. Our proposal gives way to some of the most common changes in communication made during the development and maintenance phase in IoT systems, like changing the destination of data transmission, sending the data to multiple destinations, and changing the frequency of sending data. Our solution, which is used in the programs, is loaded on the device. When the device starts, it connects to a configuration server in the background and listens for changes. The changes are sent to the configuration server using specified commands. When a change is detected, the command is processed, and the change in communication is applied without stopping the running program. We designed experiments to evaluate the complexity of the programs developed using our proposal and the actions needed to make a change.

Knowledge graphs enable semantic search in a variety of information systems. Some collaborative and public ones have existed for more than a decade. That is the case of Wikidata, one of the most popular knowledge bases today. It contains a graph of entities that has been growing since 2012 to host more than 94 million items. Currently, the exploration of data in Wikidata is a tedious task, especially for inexperienced users: it requires users to go deep into entities and perform a large number of clicks and searches of property names. Our goal is to allow nonexpert users who want to enter new data in Wikidata to be able to examine its ontologies in an agile way so that they can know whether a particular statement is present in the graph. To this end, we propose a new search box for Wikidata, which allows an exploratory search based on chained entities without having to navigate through pages. It is based on the real-time classification of the information that the user enters in the search box and the dynamic generation of suggestions based on the exploration of entities and relationships. A quantitative analysis is performed comparing how many iterations a user needs to perform a set of popular searches with our proposal and standard Wikidata search. The results suggest that interaction can be reduced by about 43%.

A corpus is a collection of texts or data used in scientific research. Its use is very common in natural language processing techniques such as keyword extraction, classification, and automatic question answering. The structure and content of a corpus can vary depending on the research field and objectives, with many being based on a common topic such as news, scientific papers, or historical documents. For some research works, the corpus must include the base texts and the keywords. The main problem is that the meaning of keywords is not the same in all fields. For example, in the context of education, keywords must be the important words that students must remember. These educational keywords do not match with the keywords in other contexts which are usually the most repeated words or the words that can be used to classify or summarize the text. There is no public corpus which includes educational texts and their keywords from the point of view of education. This could be due in part to many educational texts being books with copyright. The objective of this research work is to design an automatic tool that will be able to create a high-quality corpus for educational purposes. These tools will analyze and process textbooks that are supplied as input. The generated corpus will contain main content of the units and the keywords that are really relevant in the educational context. The analysis done by the proposal will be responsible for excluding non-relevant content for the corpus, such as exercises, test, index, etc.

Knowledge graphs enable semantic search in a variety of information systems. Some collaborative and public ones have been existing for more than a decade. That is the case of Wikidata, one of the most popular Knowledge Bases today. It contains a graph of entities that has been growing since 2012 to host more than 94 million items. As in other Linked Data projects, its data quality is a critical aspect for its usefulness, as well as being one of the objectives of this type of platform. This work focuses on one of the aspects of data quality: completeness. Our goal being to allow non-expert users who want to enter new data in Wikidata to be able to examine its ontologies in an agile way, so that they can know if a particular statement is present in its graph. To this end, we propose a new search box for Wikidata, which allows an exploratory search based on chained entities without having to navigate through its pages. This solution could enhance the user experience by decreasing the time needed to find out if a statement exists among the Wikidata entities.

Keyword extraction is an important topic applicable to a wide range of areas such as span detection, information classification, sentiment analysis, and so on. There are hundreds of algorithms which can extract keywords from text documents. Many of these algorithms also use the functionality of the keywords, which is important, especially if we need to limit to a specific area of knowledge. This research work focuses on extracting keywords from educational texts. In an educational context, the keywords are the most important parts of the lesson and may answer the professor’s questions. Classic keyword extraction algorithms have a very low success rate extracting keywords from educational texts, as the words extracted by these algorithms are very different from those selected by the teachers. Normally, the most important words from an educational point of view would not match with the most repeated words in that text. This research work attempts to improve automatic keyword extraction in educative texts, avoiding professors from having to do this tedious task. The possibility of detecting keywords automatically could be a starting point for the creation of applications capable of generating questions and exercises automatically. We tested whether the most popular word extraction algorithms were able to extract the keywords selected by professors efficiently. The result obtained by current algorithms were no good at all, as they showed a low true positive rate or very high rates of false positive. Due to these reasons, we designed a novel algorithm based on linguistic approaches and evolutive graphs. The research method to obtain the new algorithm was the design of a complex graph which operates with numerous characteristics related to the relationships between words and their linguistic properties. The graph was trained with a set of texts and keywords to establish the optimal weights for each of the characteristics. The proposal achieves a rate of true positives (TP) and F1 score significantly better than other algorithms.

Usability is a quality that a web page can have due to its simple use.Many recommendations aim to improve the web user experience, but there is no standardization of them.This study is part of a saga, which aims to order existing recommendations and guidelines by analyzing the behavior of 20 Information Technology (IT) developers.This publication analyzes the set of guidelines that determine "user responses" when they interact with a website.It is intended to group these guidelines and obtain data on the application of each of them.The test is carried out with 20 web developers without training or experience in web usability.The objective is to know if there are "user response" guidelines that a developer with no training or usability experience applies innate.Since web developers are also users, it is believed that there may be innate behavior that is not necessarily learned.The purposes of the work are: 1) Enumerate the most forgotten recommendations by web developers.This can help to think about the importance of offering specific training in this field.2) Know the most important recommendations and guidelines, according to the web developers themselves.The investigation is carried out as follows: First, IT engineers were asked to develop a website; Second, user tests were performed and the most neglected and most applied guidelines were evaluated.The level of compliance was also analyzed, as developers lack experience in web usability and could be applying a guideline, but not correctly; Third, web developers are interviewed to find out what guidelines they consider necessary.The results are intended to help us understand if a web developer without training or experience in web usability can innately apply guidelines on "user responses".The objective of the study is to determine that there are guidelines that are applied intuitively and others that are not, and to know the reason for each situation.The results determine that the guidelines considered essential and those that are most applied innately have something in common.The results reveal that the essential guidelines and those that are most commonly implemented inherently share certain commonalities.

Designing and evaluating user interfaces is a complex task. The current focus on user experience (UX) demands user-centered processes that take considerable time and resources, and thus collide with the fast-paced agile methodologies that currently dominate the industry. In this context, academia and industry have proposed the automation of different tasks in the design and evaluation user interfaces (UIs) like prototyping and user testing. Artificial intelligence (AI) techniques such as machine learning have been a considerable help to achieve this. The articles featured in this special issue describe original proposals in the use of AI for UI and user behavior evaluation.

Many Internet of Things (IoT) systems are based on the intercommunication among different devices and centralized systems. Nowadays, there are several commercial and research platforms available to simplify the creation of such IoT systems. However, developing these systems can often be a tedious task. To address this challenge, a proposed solution involves the implementation of a unified program or script that encompasses the entire system, including IoT devices functionality. This approach is based on an abstraction, integrating the control of the devices in a single program through a programmable object. Subsequently, the proposal processes the unified script to generate the centralized system code and a controller for each device. By adopting this approach, developers will be able to create IoT systems with significantly reduced implementation costs, surpassing current platforms by more than 10%. The results demonstrate that the single program approach can significantly accelerate the development of IoT systems relying on device communication.

The automatic extraction of keywords is a task frequently used in many fields of knowledge for various purposes such as email classification, text summaries, sentiment detection, and more. Among the most important factors for identifying keywords in a text are the type of text being analyzed and what is considered a keyword. For example, it is not the same to extract keywords from an e-commerce website, a set of emails, or literature books. Our interest is focused on extracting the main concepts from texts used within the educational environments of high school and university. The concepts that a student must remember do not always coincide with the most repeated words in the text or the words that would be useful for classifying a text. We will focus on these educational texts that serve as the basis for students to understand and successfully solve exercises and questions.Although there are many algorithms for keyword extraction, no algorithms have been found that focus on the specific characteristics of textbooks and extracting keywords in the context of education. Our research proposes a solution based on the use of pretrained models with transformer architecture such as BERT adapted to the structure of educational texts to be used in the future for automatic generation of test questions.

This research work is the continuation of previous, in which a set of usability guidelines where proposed. These guidelines were obtained from various authors and recommendations. The common part of those guides was that all of them were useful to reduce the noise and focus the attention of users in web interfaces. Some of these recommendations were evaluated in very confined environments, this research tries to evaluate the possible advantage of applying every one of these recommendations, quantifying in an experiment with real users what could be the potential time gain applying every of the recommendations. We have designed a set of web applications in which the user has to complete a simple task, some of the applications fill the usability guidelines and others not. With obtained data in the experiment, the web developers could choose in a more precise way which recommendations could be implemented in their interfaces to get a more efficient user interaction.

This research investigates the reasons for the lack of enrollment of women in science careers, a strong trend in Spain and many other countries. One of the branches of knowledge in which this lack of women is most noticeable in computing. The hypothesis is that parents’ academic training could influence their children’s academic training and orientation towards scientific specialities. This analysis includes the first two grades of hihg school. In the Spanish Educational System, students choose their speciality in these two final stages, so their university future is conditioned. It has designed a survey that includes questions about parents’ training and employment. One hundred sixty-eight students answered thus survey of the Baccalaureate and Technical / Professional Schools in Spain. The results and conclusions set out the necessary bases to design a tool that simulates students’ behaviour when they enrol. And identify the premises considered during the choice of studies. It would be interesting to get a system that encourages the motivation of women for scientific careers.

Plagiarism detection in all kinds of works is a recurrent problem in the educational environment, at all levels. There are many tools capable of detecting plagiarism, with most of them using a combination of different algorithms. The most basic plagiarism detection system is based on the comparison of literal text strings, with the use of more complex algorithms allowing the detection of other types of copies where authors change or alter the structure and words in order for the work to have less resemblance to the original source. In this research work, we have developed a tool that allows text comparison with different types of algorithms. Ten students were asked to copy a text trying to hide that it has been copied, and the resulting texts were analyzed with a set of algorithms included in the tool, with the objective of verifying which algorithms do not detect the plagiarism and also how much time the students required to do so.

The objective of this publication is to analyze compliance with the web usability guidelines onGiving information quickly and comprehensibly. The behavior of 20 IT engineers without experience in web usability is analyzed to collect data on the application and compliance of each of the studied guidelines. The objectives are: (1) make a list of recommendations on the presentation of information and possible actions in a quickly understandable way. And highlight the most forgotten guidelines or the worst followed by web developers to think about the importance of offering specific training in this field. (2) Know the most important guidelines according to the participants themselves. To obtain the results, user tests are performed that evaluate the most ignored and applied guidelines. And its correct compliance is studied, since the participants do not have experience in web usability. Besides, interviews are conducted to find out which are the guidelines that they consider most important. It is expected to know if there are guidelines that apply intuitively and why. It is also intended to know if this innate application is helpful or compliance is wrong and needs specific training.

Usability measures the quality of use when a user interacts with a website. There are many guidelines and recommendations to improve the user experience on websites.The purpose of this study is to analyze the degree of compliance with the well-known recommendation “follow conventions.” The behavior of 20 IT engineers is analyzed to obtain application data for each of the associated guidelines. This test is carried out with web developers without training in web usability. The purpose of the analysis is to know if there are guidelines that are applied innate. As web developers are also users, it is thought that there may be some innate behavior when applying these guidelines.The purposes of the paper are: (1) Make a list of the most forgotten recommendations by web developers to think about the importance of offering specific training in this field. (2) Know the most important recommendations according to web developers. To get the study purposes the research is carried out as follows. User tests are carried out to evaluate the most forgotten and applied proposals by the developers. Examinations are also done to determine the level of compliance since the participants lack experience in web usability. Interviews with web developers are carried out to evaluate the recommendations considered necessary.It is expected to find results that help to understand if a web developer without training in usability can innately apply guidelines on conventions. And if this native application of the guidance it is useful. We want to show that there are guidelines that are used intuitively. And that there are guidelines that do not apply, and the reason for each situation.The results indicate that the guidelines considered essential and those most applied by web developers without training have something in common. All of them focus on design and seek to design and adjust to known standards that facilitate user navigation.