This paper presents a novel framework for accessible and pedagogically-grounded robot explainability, designed to support human–robot interaction (HRI) with users who have diverse cognitive, communicative, or learning needs. We combine principles from Universal Design for Learning (UDL) and Universal Design (UD) with symbolic communication strategies to facilitate the alignment of mental models between humans and robots. Our approach employs AsTeRICS Grid and ARASAAC pictograms as a multimodal, interpretable front-end, integrated with a lightweight HTTP-to-ROS 2 bridge that enables real-time interaction and explanation triggering. We emphasize that explainability is not a one-way function but a bidirectional process, where human understanding and robot transparency must co-evolve. We further argue that in educational or assistive contexts, the role of a human mediator (e.g., a teacher) may be essential to support shared understanding. We validate our framework with examples of multimodal explanation boards and discuss how it can be extended to different scenarios in education, assistive robotics, and inclusive AI.

Abstract The use of haptic simulation for emergency procedures in nursing training presents a viable, versatile and affordable alternative to traditional mannequin environments. In this paper, an evaluation is performed in a virtual environment with a head-mounted display and haptic devices, and also with a mannequin. We focus on a chest decompression, a life-saving invasive procedure used for trauma-associated cardiopulmonary resuscitation (and other causes) that every emergency physician and/or nurse needs to master. Participants’ heart rate and blood pressure were monitored to measure their stress level. In addition, the NASA Task Load Index questionnaire was used. The results show the approved usability of the VR environment and that it provides a higher level of immersion compared to the mannequin, with no statistically significant difference in terms of cognitive load, although the use of VR is perceived as a more difficult task. We can conclude that the use of haptic-enabled virtual reality simulators has the potential to provide an experience as stressful as the real one while training in a safe and controlled environment.

Cyberattacks are a growing concern for companies and public administrations. The literature shows that analyzing network-layer traffic can detect intrusion attempts. However, such detection usually implies studying every datagram in a computer network. Therefore, routers routing a significant volume of network traffic do not perform an in-depth analysis of every packet. Instead, they analyze traffic patterns based on network flows. However, even gathering and analyzing flow data has a high-computational cost, and therefore routers usually apply a sampling rate to generate flow data. Adjusting the sampling rate is a tricky problem. If the sampling rate is low, much information is lost and some cyberattacks may be neglected, but if the sampling rate is high, routers cannot deal with it. This paper tries to characterize the influence of this parameter in different detection methods based on machine learning. To do so, we trained and tested malicious-traffic detection models using synthetic flow data gathered with several sampling rates. Then, we double-check the above models with flow data from the public BoT-IoT dataset and with actual flow data collected on RedCAYLE, the Castilla y León regional academic network.

SQL injections rank in the OWASP Top 3. The literature shows that analyzing network datagrams allows for detecting or preventing such attacks. Unfortunately, such detection usually implies studying all packets flowing in a computer network. Therefore, routers in charge of routing significant traffic loads usually cannot apply the solutions proposed in the literature. This work demonstrates that detecting SQL injection attacks on flow data from lightweight protocols is possible. For this purpose, we gathered two datasets collecting flow data from several SQL injection attacks on the most popular database engines. After evaluating several machine learning-based algorithms, we get a detection rate of over 97% with a false alarm rate of less than 0.07% with a Logistic Regression-based model.

Haptic devices can be used to feel through the sense of touch what the user is watching in a virtual scene. Force feedback devices provide kinesthetic information enabling the user to touch virtual objects. However, the most reasonably priced devices of this type are the desktop ones, which have a limited workspace that does not allow a natural and convenient interaction with virtual scenes due to the difference in size between them and the workspace. In this paper, a brand-new interaction model addressing this problem is proposed. It is called Haptic Zoom and it is based on performing visual and haptic amplifications of regions of interest. These amplifications allow the user to decide whether s/he wants more freedom in movements or an accurate interaction with a specific element inside the scene. An evaluation has been carried out comparing this technique and two well-known desktop haptic device techniques. Preliminary results showed that haptic zoom can be more useful than other techniques at accuracy tasks.

This paper describes the integration of haptics support into a virtual reality training simulation aimed at skills retention for paramedics. We focus on a chest decompression, a life-saving invasive procedure used for trauma-associated cardiopulmonary resuscitation (and other causes) that every emergency physician needs to master. It is not regularly performed by a paramedic, however, and therefore skills maintenance is a challenge. In our simulation, a virtual Russell PneumoFix-8 device is used to carry out the procedure and it is controlled with the 3D Systems Touch grounded force feedback device. We describe how this device has been integrated into an immersive virtual environment so that it or any other tool can be used at any location in the scene. Quantitative data has been obtained from an evaluation exercise carried out with 21 paramedics. The majority of these participants reported a good feeling of presence, according to the Spatial Presence Experience Scale. They indicated strongly that the use of haptic-enabled simulators that include the kind of interaction techniques implemented in our simulator would be beneficial for training and skills retention. The realism of using the simulator at a 1 to 1 scale was also highly scored. A System Usability Scale was also calculated and the results show that the simulator is close to an acceptable standard for usability but more work is needed. We will address this in future work.

Abstract The integration of a Supercomputer in the educational process improves student’s technological skills. The aim of the paper is to study the interaction between science, technology, engineering, and mathematics (STEM) and non-STEM subjects for developing a course of study related to Supercomputing training. We propose a flowchart of the process to improve the performance of students attending courses related to Supercomputing. As a final result, this study highlights the analysis of the information obtained by the use of HPC infrastructures in courses implemented in higher education through a questionnaire that provides useful information about their attitudes, beliefs and evaluations. The results help us to understand how the collaboration between institutions enhances outcomes in the education context. The conclusion provides a description of the resources needed for the improvement of Supercomputing Education (SE), proposing future research directions.

STEAM Education is nowadays a key element for our current digital society. Integrating STEAM and developing competences such as Computational Thinking is highly demanded by the industry and higher education institutions. In order to do so new methodological approaches are required. RoboSTEAM project is an Erasmus+ project defined to address these topics by using of physical devices and robotics employing Challenge Based Learning methodology. One of the first steps in the project development is the definition of current landscape in the research field. Which means to carry out a literature mapping that considers previous applications of Challenge Based Learning in STEAM education and use of robots and physical devices to do so. This paper shows the mapping review process and the main results obtained. The mapping analyze 242 candidate works from the most relevant bibliographic sources and selected 54. Form them it was possible to see that there are not many initiatives on STEM Education related to Challenge base learning and the most of them are specially focused on the application of specific tools and in the development of concrete competences.

The development of a learning system based on integrating a number of learning services needs both a technological platform to support the system as well as a methodology that manages the development process. Such technological platform is provided by the Service Oriented Learning Architecture (SOLA) that defines an architecture style guiding several aspects of deploying units of learning that are packaged as services. The purpose of this paper is to review the SOLA concept and present a specific methodology, based on analysing instructional domains, to complement the SOLA approach. The method here proposed addresses the identification and classification of learning services to facilitate the integration of such services.

Instructional software can be defined as any computer program used for instruction. As a means to optimise the development process of instructional software, different authors have defined a range of methods based on Software Engineering. However, the use of a method does not guarantee the validity and quality of the product developed; hence, a series of Software Process Improvement (SPI) approaches aimed to improve and guarantee the development process that have arisen. The purpose of this paper is to review the aforementioned approaches and to apply them to the analysis phase of the instructional software development process. The analysis phase aims to define the conditions and needs of the project in order to solve uncertainties in early stages of the process.

The analysis phase constitutes an essential step in the development of information systems. Nevertheless, learning materials design activities currently have reduced the analysis phase to a narrative description of particular learning problems. The intention of this paper is to highlight the relevance of the analysis phase within the learning material development process. To this end, we introduce the concept of "Learning Analysis" as the set of mechanisms that enable us to analyze the design space based on a wellknown domain model.

It is not always possible to foresee all properties values of a learning design process at design-time. Sometimes, it is not until its proper execution when those values can be established. Besides, some of the original definitions must be modified to adapt the learning process to its current execution context. This is especially necessary with properties related to the synchronization and temporization of the different activities that constitute the learning process. Due to the above, to successfully implement a learning process, the designers need to use a language expressive enough to allow a detailed description of the runtime behavior of the course and a mechanism to modify its definition during run-time.

In the last years several learning systems have been developed trying, on a different extent, to develop a solution to the problem of personalization of the learning process. Their objective is to provide the learner with a learning system able to adapt the course to her specific characteristics, knowledge, objectives and learning goals. Further more, we would like a learning system that could be sensitive to the context in which the learning session is taking place and capable to adjust the appropriate parameters accordingly. Taking this into account, the authors have selected a group of desirable characteristics for an ideal learning system and have reviewed some of the solutions developed in the last years trying to find out which of those ideal characteristics have already been implemented and which others have not.