Engineering education

Natural disasters have a significant effect in terms of impacted individuals and casualties. Artificial Intelligence (AI) techniques for automatically segmenting landslides from aerial photos is a relatively new field of research. Segmenting landslips quickly and accurately can significantly aid in assessing the damage caused by natural disasters. This research aims to compare the performance of AI techniques with more classical methods for the automatic segmentation of landslides from aerial images for damage assessment. It is presented a dataset of satellite images containing landslides collected in the Broni (Italy) region and annotated to train and test the segmentation model. Both classical image processing techniques, such as thresholding and edge detection, and AI-based methods, such as U-Net, are applied to the dataset. Overall, this research demonstrates that AI-based methods are a promising tool for automatically segmenting landslides from aerial images and can be a powerful asset in assessing the damage caused by natural disasters. The study also highlights the importance of combining classical and AI-based methods for better performance, especially in challenging and complex scenes.

Keywords: Artificial Intelligence , Damage Assessment , Landslips , Semantic Segmentation

Surgical operations must be preformed by skilled and qualified personnel. Training is therefore of paramount importance to master enough skill to succeeds in the tasks without endangering the health of the patients. Combining different types of training activities, can help reaching the goal in a quicker and more effective way. In this scenario, Virtual Reality represents an interesting step, particularly thanks to the reduction in the cost of the equipment that have made their adoption affordable and their availability widespread. In this work, we present our advances in training lung operations with low-cost virtual reality simulation environments.

Keywords: Simulation , surgical operations , training , Virtual reality

This paper introduces a unique, feature-based methodology for determining the best design features of a Virtual Reality Training System (VRTS). It offers a holistic approach by using a revised Technology Acceptance Questionnaire, which assesses design features from a user's perspective, rather than relying solely on objective measures of training effectiveness. We implemented the methodology in an experimental campaign, which involved simulating manual processes in two VR platforms with different features. Both novice and experienced VR users participated in the study, evaluating design features for perceived usefulness and ease of use. The findings provide insights into improving VRTS design based on user experience, highlighting the potential of our feature-based methodology.

Keywords: Design Features , Manual Layup , Technology Acceptance , User Experience , Virtual Reality , Virtual Training

In response to the increasing number of traffic accidents, industrialized countries are investing in educational programs to raise awareness of safe driving. The most common type of intervention to reduce risky driving behaviors is the showing of traumatic experience videos related to the occurrence of traffic accidents caused by incorrect and high-risk driving habits. However, the effectiveness of this intervention depends on several factors, including how this content is experienced. Nowadays, thanks to Cinematic Virtual Reality (CVR) technologies, new modalities of video content fruition can be exploited. In this work, we implemented a CVR application to show 360° videos of traffic accidents and evaluate the effectiveness of CVR as an educational intervention tool to improve drivers' attitudes toward traffic safety. A sample of 86 users aged 18 to 56 years answered a questionnaire on Attitudes Toward Traffic Safety Scale (ATTSS) administered before and after the CVR experience. In addition, a user experience questionnaire (UEQ) was administered. The results analysis of ATTSS questionnaires shows that the CVR experience increases risk awareness by inducing greater attention to safety while driving. Finally, the results of the UEQ questionnaire reveal that users positively evaluate the experience of using the system from hedonistic, pragmatic, and usability perspectives.

Keywords: 360 video , Educational Intervention , Traffic Safety , Virtual Reality

The use of large language models (LLMs) is now spreading in several areas of research and development. This work is concerned with systematically reviewing LLMs' involvement in engineering education. Starting from a general research question, two queries were used to select 370 papers from the literature. Filtering them through several inclusion/exclusion criteria led to the selection of 20 papers. These were investigated based on eight dimensions to identify areas of engineering disciplines that involve LLMs, where they are most present, how this involvement takes place, and which LLM-based tools are used, if any. Addressing these key issues allowed three more specific research questions to be answered, offering a clear overview of the current involvement of LLMs in engineering education. The research outcomes provide insights into the potential and challenges of LLMs in transforming engineering education, contributing to its responsible and effective future implementation. This review's outcomes could help address the best ways to involve LLMs in engineering education activities and measure their effectiveness as time progresses. For this reason, this study addresses suggestions on how to improve activities in engineering education. The systematic review on which this research is based conforms to the rules of the current literature regarding inclusion/exclusion criteria and quality assessments in order to make the results as objective as possible and easily replicable.

Keywords: engineering education , large language models—LLMs , LLM-based tools , PRISMA , systematic review

This study proposes a ground-breaking idea at the intersection of Artificial Intelligence and virtual education: the creation of an AI-powered Digital Twin instructor in a Metaverse-based classroom using Large Language Models. We aim to build a teacher avatar capable of dynamic interactions with students, tailored teaching approaches, and contextual response inside a virtual world. The research aims to address two major issues for both students and teachers: the Digital Twin can provide feedbacks to resolve doubts about course content and material; also, it can improve student management and allow teachers to answer the trickiest questions raised by students.

Keywords: Artificial intelligence , Computer education programs , Computer-assisted instruction , dialogue and pragmatics Applied computing , Discourse , Education , Natural language processing , Professional topics , Social and professional topics , Software engineering education; Computing methodologies

Designers need to be aware early in the design phase of the environmental impact of their choices over the entire product life cycle. This paper proposes an eco-design method to support designers of different categories of electric vehicles, such as self-driving vehicles, cars, shuttles and buses. The methodology developed aims to realize a model for predicting the environmental impact of industrial electric vehicles. The proposed approach exploits machine learning methods to develop models with the design features of a generic electric vehicle, such as vehicle mass and distance traveled during its entire lifetime as independent parameters, to estimate the emissions of new products. The environmental impact indicator for this study is Climate Change, the dependent parameter chosen for the impact model. Machine learning algorithms were trained on training data retrieved from an automatic environmental impact estimation software tool based on an analytical approach. All stages of the product life cycle have been considered in the construction of the database, and the model provides quantitative results that consider the consumption of material and energy resources. Finally, the model is tested by estimating the environmental impact of a tourist shuttle.

Keywords: Data Science , Design , Life Cycle Assessment , Machine Learning , Sustainability

Virtual Training (VT) is a recently available modality that uses Virtual Reality (VR) technologies to train people within simulated environments. Companies can use VT to leverage the skills of their staff by avoiding risks related to real production thanks to the digital simulation possibilities and anticipating the training phases to reduce downtime of productive systems [1]. However, the use of VR-based immersive training is still limited in industry due to the cost of equipment and the lack of skilled people able to use VR platforms to effectively implement this type of simulations. This paper deals with the application of low-cost VR equipment to develop virtual training applications. It defines a methodology to create suitable applications for smartphones to be displayed by low-cost, highly portable Google Cardboard. Such equipment could be easily used also by small and medium-sized enterprises (SMEs) that do not have large capitals to invest in traditional VR viewers but are still interested in exploring the adoption of digital tools for training. A case study is presented related to assembly of a 3D printer.

Keywords: Digital Simulation , Ergonomics , Human-centered de-sign , Virtual training , X-reality

Background: Several studies have demonstrated the effectiveness of telerehabilitation. However, it remains unclear what proportion of people in need of rehabilitation can confidently use telecommunications networks and related devices. Objectives: The aim of this study is to estimate the proportion of patients who possess either the requisite digital literacy to perform telerehabilitation independently or have a family caregiver capable of providing effective support. Methods: Synthetic populations with a realistic kinship network (i.e. family trees) representative of European countries are built. Age, sex, and location-specific prevalence rates of rehabilitation needs and digital skills are combined to estimate the percentage of digitally literate patients and patients with digitally literate relatives. Results: In Europe, 86% of people in need of rehabilitation are potentially eligible for telerehabilitation. However, in four out of five cases, eligible patients over the age of 65 require caregiver support. Conclusion: Telerehabilitation has the potential to spread in Europe. Caregivers have an essential social role in ensuring sustainable access to telerehabilitation.

Keywords: Caregivers , Kinship Care , Sustainable Development , Telemedicine , Telerehabilitation

While Blue Economy remains a fundamental sector in many world economies, its needs and impacts require specialized skills. For the sustainability of blue economy sectors, both technical skills (blue and digital) and green skills are needed. Identifying a skills gap, the uBlueTec project aims to set up, test and validate a triple transition training and skills development model (green, blue, digital skills). Through a durable partnerships among universities, VET providers, clusters and Small and Medium Entreprises (SMEs), the project will developed curricula and implement pilots both for VET and Higher Education levels. The article describes the skills gaps analysis and preliminary work on the curricula.

Keywords: blue economy , blue skills , digital skils , robotics education , underwater technologies , VET training

This book guides the reader through the process of graphic communication with a particular focus on representing data and processes. It considers a variety of common graphic communication scenarios among those that arise most frequently in practical applications. The book is organized in two parts: representing data (Part I) and representing processes (Part II). The first part deals with the graphical representation of data. It starts with an introductory chapter on the types of variables, then guides the reader through the most common data visualization scenarios – i.e.: representing magnitudes, proportions, one variable as a function of the other, groups, relations, bivariate, trivariate and geospatial data. The second part covers various tools for the visual representation of processes; these include timelines, flow-charts, Gantt charts and PERT diagrams. In addition, the book also features four appendices which cover cross-chapter topics: mathematics and statistics review, Matplotlib primer, color representation and usage, and representation of geospatial data. Aimed at junior and senior undergraduate students in various technical, scientific, and economic fields, this book is also a valuable aid for researchers and practitioners in data science, marketing, entertainment, media and other fields.

Keywords: Data Visualization , Graphic Communication , Matplotlib , Process Visualization , Python Programming , Seaborn

Conducting thoracoscopic surgery necessitates a high level of skill and specialized training. In addition to practicing on actual patients, surgeons utilize various safer training methods. A widely used training apparatus is the laparoscopic box, which contains multiple compartments fitted with training modules to replicate diverse surgical scenarios accurately. Unfortunately, the cost of these devices can be prohibitively high, making it challenging for individual students to acquire their own. Virtual Reality has emerged as a promising solution, especially due to the decreasing costs of VR equipment, which makes it more accessible. This study details our progress in enhancing training for lung surgeries by leveraging cost-effective VR technologies with head-mounted displays. In particular, simulations of thoracoscopic surgery scenarios within a VR environment have been developed, aiming to create training exercises that serve as an initial step before advancing to laparoscopic simulation boxes and, ultimately, actual surgical procedures on patients. For reproducing the behaviour of the soft lung tissues, we used a recent version of the Extended Position-Based Dynamics (XPBD) model, which solves some of the known problems encountered in the traditional PBD system, thereby enhancing the realism of the simulation.

Keywords: Position-based Dynamics , Training , Virtual Reality

This research consists in a detailed analysis of the ISO Geometrical Product Specifications (GPS) system's knowledge and usage in Italy. Data was collected by means of a questionnaire, from a wide range of industrial sectors and academic institutions. The dataset encompasses 143 responses, forming the basis for an in-depth examination of ISO GPS system implementation in Italy. This analysis involves three levels of comparison: (1) an examination of knowledge level and typical usage between Beginners and Experienced individuals, (2) an investigation into ISO GPS adoption patterns in Industry and Academia, with and without specific ISO GPS training, and (3) an exploration of differences among professionals who are responsible for conveying geometric specifications and those in charge of interpreting and applying them. The findings reveal significant insights into ISO GPS implementation in both academic and industrial domains. They highlight the need for the improvement of ISO GPS education offer and the development of more effective utilization practices, with potential implications for future ISO GPS standards development strategies.

Keywords: Geometric Specifications Management , Geometrical Product Specifications , ISO GPS , Training

Functional evaluation plays an important role in determining suitable training programs for elite athletes. For athletes with Intellectual Impairment, it may represent an even more powerful tool as it allows to obtain quantitative feedbacks (when qualitative ones are hard to collect). This study presents practical examples in the context of strength assessment tests carried out in the functional evaluation project of the Italian Sport Federation for athletes with Intellectual Impairment (FISDIR). In particular, a useful customized tool for the assessment of explosive strength in sprinters, based on biomechanical indices, is presented. The proposed approach starts with the definition of key biomechanical parameters in terms of spatiotemporal, kinematic, kinetics, energetic and joint angles related to each main phase of the test. According to the literature and technical recommendations, reference target values for each parameter are defined and normalized. In addition, a quick graphical visualization was designed. Finally, two synthetic indices related to the performance and execution are developed. Practical implications in squat jump test are presented. The proposed methodology represents a useful customized tool for improving training in athletes with Intellectual Impairment.

Keywords: biomechanics , Functional evaluation , intellectual impairment , strength assessment

This research investigates the possible influence of students' perceptions of emerging AI technologies on university courses, focusing on their knowledge and perceived usefulness within engineering design. An evaluation tool implemented in a Microsoft Excel workbook was developed and tested to perform the process of data collection through well-known questionnaires, data analysis, and the generation of results, facilitating attention to class compositions and measuring AI awareness and perceived usefulness. The study considers traditional aspects such as roles within design teams and the psychological factors that may influence these roles, alongside contemporary topics like Large Language Models (LLMs). Questionnaires based on well-established theories were administered during courses on product innovation and representation, assessing both primary and secondary design roles. Primary roles focus on technical skills and knowledge, while secondary roles emphasize problem-solving approaches. The Big Five questionnaire was used to characterize students' psychological profiles based on the main personality traits. Students' perceptions of AI involvement and usefulness in engineering design were evaluated using questionnaires derived from the consolidated literature as well. Data were collected via Google forms from both in-class and off-line students. The first results of the workbook adoption highlight some relationships between personality traits, perceived roles in design teams, and AI knowledge and usefulness. These findings aim to help educators enhance course effectiveness and align courses with current AI advancements. The workbook is available to the readers to collect data and perform analyses in different countries, education disciplines, and as time goes by, in order to add the longitudinal point of view to the research.

Keywords: artificial intelligence—AI , engineering design , engineering education , evaluation tools , Gen Z , Large Language Models—LLMs , product innovation , product representation

The future is bright and challenging: we envision a very complex combination of mixed reality (MR), artificial intelligence, and spatial computing as a smart integration of interconnected systems—seamlessly bridging both physical and virtual spaces. The upcoming generation of everyday wearable, embedded, and ubiquitous technology allows the ideation and validation of a wide range of next-generation context-aware, or intelligent MR user experiences. Realization of this vision is promising, especially given recent interdisciplinary advancements in key areas and growing interest in applying novel approaches in real-world application domains. This Special Issue aimed to attract ambitious contributions addressing this intelligent vision for MR leveraging, new computational interfaces, spatial computing, rich and diverse data sources, smart devices' extensive computation power, artificial intelligence, and sensing capabilities, as well as ubiquitous connectivity, computation resources, and storage offered by the existing communication and network infrastructure. We sought contributions that addressed new methods, technologies, approaches, applications, case studies, and industrial showcases, paving the way for novel insights, breakthrough designs, discussions, and developments in this rapidly evolving domain.

The advent of Industry 4.0 has led to the need to train highly skilled operators in complex and dynamic environments, through the convergence of physical and digital technologies. In this context, indoor navigation plays a crucial role in the training of Operators 4.0, allowing them to acquire spatial knowledge and specific skills to operate effectively in advanced industrial environments. However, the challenges associated with this technology, such as environmental complexity and obstacles, require an innovative approach to operator training. Mixed Reality (MR) represents a promising technological innovation for the development of these systems. Indeed, MR enables the co-represence of digital and real world, by content overlapping and integrated interaction between virtual and real assets, promoting efficiency, safety and user engagement. Within this scenario, the paper proposes a Holographic Navigation (HoloNav) methodology based on spatial and cloud computing for the development of an indoor navigation application according to a transdisciplinary approach. The application is deployed on the Microsoft HoloLens 2 as MR device, using Microsoft Azure Spatial Anchors (ASA) and Cloud Storage Account resources. This study aims to provide an applied methodology and guidelines for application development, and to analyze the broader social implications and potential for social change of such MR technology to support training processes. The proposed ASA-based HoloNav approach was applied through a case study, where a tour inside the spare parts warehouse was developed for new operators who need to start familiarizing themselves with all the different areas.

Keywords: Indoor navigation , Microsoft HoloLens 2 , Mixed reality , Transdisciplinary engineering , User experience

Italian Sign Language (LIS) is the primary form of communication for many members of the Italian deaf community. Despite being recognized as a fully fledged language with its own grammar and syntax, LIS still faces challenges in gaining widespread recognition and integration into public services, education, and media. In recent years, advancements in technology, including artificial intelligence and machine learning, have opened up new opportunities to bridge communication gaps between the deaf and hearing communities. This paper presents a novel educational tool designed to teach LIS through SIGNIFY, a Machine Learning-based interactive serious game. The game incorporates a tutorial section, guiding users to learn the sign alphabet, and a classic hangman game that reinforces learning through practice. The developed system employs advanced hand gesture recognition techniques for learning and perfecting sign language gestures. The proposed solution detects and overlays 21 hand landmarks and a bounding box on live camera feeds, making use of an open-source framework to provide real-time visual feedback. Moreover, the study compares the effectiveness of two camera systems: the Azure Kinect, which provides RGB-D information, and a standard RGB laptop camera. Results highlight both systems' feasibility and educational potential, showcasing their respective advantages and limitations. Evaluations with primary school children demonstrate the tool's ability to make sign language education more accessible and engaging. This article emphasizes the work's contribution to inclusive education, highlighting the integration of technology to enhance learning experiences for deaf and hard-of-hearing individuals.

Keywords: gamification , gesture recognition , hand sign alphabet , machine learning , serious game , social inclusion

In an era characterized by the increasing complexity of products and the rapid turnover of the workforce across different companies, there is a growing need to invest significantly in quick and efficient training methods. Concurrently, the advancement of digitalization has rendered certain training practices anchored to paper-based materials obsolete. Numerous companies are directing their investments toward digital training, yet the optimal format to exploit the full advantages of digitalization remains unclear. This study undertakes a comparison of four distinct digital versions of the same training process with the aim of comprehending the tangible benefits.

Keywords: virtual and augmented reality environments , virtual prototyping

This paper presents a pioneering pilot study conducted at ARGOR-HERAEUS SA, focusing on integrating Augmented Reality (AR) HoloLens technology for emergency training and management in the scrubber System. The scrubber system, known for its relevance in terms of reducing pollutants and thus its potential dangers in case of malfunction, poses unique challenges for emergency preparedness and response. The study utilizes Unity3D to develop immersive training scenarios and emergency situations, enhancing trainee preparedness.

Keywords: ARGOR-HERAEUS SA , Augmented Reality , Emergency Management , Emergency Training , HoloLens , Pilot Study , Scrubber System , System Usability Scale (SUS) , Unity3D