As the climate crisis escalates, immersive media are increasingly viewed as promising tools for making environmental risks feel psychologically closer. Yet, empirical evidence on whether immersive media reduce psychological distance (PD) and foster pro-environmental engagement remains fragmented, heterogeneous, and theoretically inconsistent. This systematic review and meta-analysis synthesizes empirical research examining how immersive media shape PD from environmental risks, and whether such effects are associated with pro-environmental engagement. Drawing on Construal Level Theory (CLT), we examine effects across spatial, temporal, social, and hypothetical dimensions of PD, while distinguishing cognitive, affective, attitudinal, and behavioral forms of pro-environmental engagement. The review analyzes the methodological characteristics of existing research, the design strategies through which immersive media attempt to reduce perceived distance, as well as the consistency of reported effects. Meta-analytic findings indicate a small but statistically significant overall effect of immersive media on PD and pro-environmental engagement. Effects appeared comparatively stronger for temporal and hypothetical dimensions of PD, as well as for the cognitive and affective forms of pro-environmental engagement. However, the evidence does not support a consistent or direct relationship between reductions in PD and downstream pro-environmental engagement, suggesting that psychological proximity alone is insufficient to explain environmental responses. Overall, the findings indicate that immersive media are not uniformly effective proximizing tools. The paper concludes by reflecting on these findings and outlining directions for future research, emphasizing that the impact of immersive media is highly context-dependent and shaped by methodological choices, design features, individual differences and broader psychological mechanisms.

Walking has always been a primary mode of transportation and is recognized as an essential activity for maintaining good health. Despite the need for safe walking conditions in urban environments, sidewalks are frequently obstructed by various obstacles that hinder free pedestrian movement. Any object obstructing a pedestrian's path can pose a safety hazard. The advancement of pervasive computing and egocentric vision techniques offers the potential to design systems that can automatically detect such obstacles in real time, thereby enhancing pedestrian safety. The development of effective and efficient identification algorithms relies on the availability of comprehensive and well-balanced datasets of egocentric data. In this work, we introduce the PEDESTRIAN dataset, comprising egocentric data for 29 different obstacles commonly found on urban sidewalks. A total of 340 videos were collected using mobile phone cameras, capturing a pedestrian's point of view. Additionally, we present the results of a series of experiments that involved training several state-of-the-art deep learning algorithms using the proposed dataset, which can be used as a benchmark for obstacle detection and recognition tasks. The dataset can be used for training pavement obstacle detectors to enhance the safety of pedestrians in urban areas.

The increase of the percentage of elderly population in modern societies dictates the use of emerging technologies as a means of supporting elder members of the society. Within this scope, Extended Reality (XR) technologies pose as a promising technology for improving the daily lives of the elderly population. This paper presents a literature review that describes the most common characteristics of the physical and mental state of the elderly, allowing readers, and specifically XR developers, to understand the main difficulties faced by elderly users of extended reality applications so they can develop accessible, user friendly and engaging applications for the target audience. Furthermore, a review of existing extended reality applications that target the elder population is presented, allowing readers to get acquainted with existing design paradigms that can inspire future developments.

Virtual Reality (VR) technology has the potential to provide end-user teachers with highly engaging and immersive experiences that reflect real-life classroom challenges and, at the same time, offer a safe space for hands-on practice and experimentation, allowing mistakes without potential consequences to the class or the fear of affecting actual students. The appearance of the virtual environment is a significant component of user experience, and a carefully designed virtual environment customized to meet the needs of end-users can considerably enhance their experience. This paper aims to reflect on the co-design journey of a VR-based teacher training solution designed by teachers, for teachers. Teachers were actively engaged as co-designers throughout all phases of design—conceptualization, development, testing, and iteration—to ensure that the final VR training tool is aligned with their actual needs and preferences, maximizing the added value and acceptance of the virtual solution. The paper presents findings from a series of user engagement activities, highlighting the diverse perspectives of teachers and the design insights gained from their involvement. Teachers who spend a significant amount of time in classrooms may benefit more from an imaginative space rather than a standard classroom environment. The findings indicate that imaginary virtual classroom settings generate high levels of presence, indicating that users may look for experiences that break from the ordinary.

Addressing the lack of knowledge on sustainability and the 17 United Nations Sustainable Development Goals (UN-SDGs) is essential for global development. Emerging technologies hold immense potential for educating and training in SDGs. This paper presents a pilot project in higher education applying the Design Thinking Methodology to design a novel Virtual Reality (VR) training solution to raise awareness about sustainability and the UN-SDGs through handson experiential training. The paper presents the design journey for designing the VR environment prototype focusing on three SDGs advancing through five phases (Research and Empathize, Define, Ideate, Prototype, and Test). Preliminary results highlight the urgent need for immersive educational resources on sustainability and the SDGs, with VR-based training showing promising potential. Low-fidelity 2D and 3D prototypes presented as the first step of designing and developing a VR-based training solution on three selected SDGs demonstrate the opportunities of adopting VR for promoting UN-SDGs. Creating such an innovative VR training tool will advance theoretical and practical realms enhancing understanding of the 17 SDGs through immersive experiences.

The aim of the work presented in this paper is to develop and evaluate an integrated system that provides automated lecture style evaluation, allowing teachers to get instant feedback related to the goodness of their lecturing style. The proposed system aims to promote improvement of lecture quality, that could upgrade the overall student learning experience. The proposed application utilizes specific measurable biometric characteristics, such as facial expressions, body activity, speech rate and intonation, hand movement, and facial pose, extracted from a video showing the lecturer from the audience point of view. Measurable biometric features extracted during a lecture are combined to provide teachers with a score reflecting lecture style quality both at frame rate and by providing lecture quality metrics for the whole lecture. The acceptance of the proposed lecture style evaluation system was evaluated by chief education officers, teachers and students regarding the functionality, usefulness of the application, and possible improvements. The results indicate that participants found the application novel and useful in providing automated feedback regarding lecture quality. Furthermore, the performance evaluation of the proposed system was compared with the performance of humans in the task of lecture style evaluation. Results indicate that the proposed system not only achieves similar performance to human observers, but in some cases, it outperforms them.

Strong interaction between instructors and students during online course delivery is essential for supporting the educational experience. As part of the efforts to maximize the interaction between educators and students, a pilot application that monitors the actions of the students in online courses while protecting as much as possible students' privacy was developed. The purpose of the present research is to determine whether the proposed application for monitoring is acceptable to the stakeholders involved in online classes and whether this application can contribute to the enhancement of the educational experience. As part of the research, the application was evaluated by 75 participants, which included students, parents, and educators, ensuring that the views of the main stakeholders in the educational process are considered. Before the intervention, an online questionnaire was completed by the participants, who then watched a video about the function of the application and/or used the actual application. After the intervention, the participants completed an online questionnaire with similar questions. The results indicate that the use of student action recognition systems is feasible in online courses and accepted by teachers, students, and parents. Based on the results, most participants believe that the proposed application can contribute to the enhancement of the efficiency of distance education with regard to the student active participation, concentration level, learning results, teacher-student interaction, students' interest, and students' evaluation.

Virtual reality (VR) can be useful in efforts that aim to improve the well-being of older members of society. Within this context, the work presented in this paper aims to provide the elderly with a user-friendly and enjoyable virtual reality application incorporating memory recall and storytelling activities that could promote mental awareness. An important aspect of the proposed VR application is the presence of a virtual audience that listens to the stories presented by elderly users and interacts with them. In an effort to maximize the impact of the VR application, research was conducted to study whether the elderly are willing to use the VR application and whether they believe it can help to improve well-being and reduce the effects of loneliness and social isolation. Self-reported results related to the experience of the users show that elderly users are positive towards the use of such an application in everyday life as a means of improving their overall well-being.

The body language of an educator during a class can affect student’s level of interest and concentration. As an attempt to assist educators to improve their body language and speaking characteristics, a pilot body language analysis system that assesses the body language of educators was developed. The proposed application makes use of specific biometric features for determining body language quality during class delivery. The aim of the current study is to examine whether the proposed application can contribute to improving the teachers’ body language, whether the application can provide satisfactory feedback related to the teachers’ body language, and whether the use of the application in real classroom conditions is acceptable. As part of this effort the pilot application has been assessed by teachers of primary, secondary and university education. The experimental investigation involved two phases. In the first phase participants delivered a short lecture that was evaluated using the automated body language analysis application. After the lecture participants were informed about the operation of the application and they were presented with the feedback generated by the body language analysis. During the second phase participants delivered a second short lecture. By comparing the body language quality between the two phases, conclusions related to the impact of the application in improving body language were derived. Experimental results demonstrate that the application provides satisfactory feedback, it is acceptable to use the application in real class conditions, and the feedback provided can be used for self-assessment, reflection and improvement regarding educator’s body language.

The use of the latest developments in Artificial Intelligence (AI) in various professional fields is becoming more noticeable these days. New trends require professionals to adapt the new reality and make effective use of AI technologies. In the case of journalism, generative AI tools enhance the automatic creation of journalistic content by enabling personalized news as well as real-time reporting. While AI can be used in newsrooms to aid the demanding work of journalists and reduce costs for news organizations, its integration raises significant ethical, legal and quality control concerns, including issues of quality, bias, authenticity, and intellectual property. Recent advances in AI, such as deep learning and computer vision, have shown significant potential in the creation of highly aesthetic visual material. In this article we focus on the transformative impact of AI generative tools on visual journalism, and we present the opportunities as well as the challenges arising from their use, identifying both advantages and disadvantages for visual journalism.

ON THE DEVELOPMENT OF A VIRTUAL REALITY TEACHER TRAINING APPLICATION: INSPIRED BY EDUCATORS, DESIGNED FOR EDUCATORS

Walking has been widely promoted by various medical institutions as a major contributor to physical activity that keeps people healthy. However, pedestrian safety remains a critical concern due to barriers present on sidewalks, such as bins, poles, and trees. Although pedestrians are generally cautious, these barriers can pose a significant risk to vulnerable groups, such as the visually impaired and elderly. To address this issue, accurate and robust computer vision models can be used to detect barriers on pedestrian pathways in real-time. In this study, we assess the performance of fine-tuned egocentric barrier recognition models under various conditions, such as lighting variations, angles of view, video frame rates and levels of obstruction. In this context, we collected a dataset of different barriers, and fine-tuned two representative image recognition models, assessing their performances on a set of videos taken from a predefined route. Our findings provide guidelines for retaining model performance for applications using barrier recognition models in varying environmental conditions.

An integrated system that provides automated lecture style evaluation, allowing teachers to get instant feedback related to the goodness of their lecturing style is presented. The proposed system aims to promote quality improvement of lecture delivery, that could upgrade the overall learning experience of students. The proposed application focuses on specific measurable biometric characteristics, such as facial expressions, body activity, speech rate and intonation, hand movement and facial pose, extracted through video and audio. Measurable biometric features extracted during a lecture are combined to provide teachers with a score reflecting lecture style quality both at frame rate and by providing quality metrics for the whole lecture. A pilot evaluation of the application was conducted with chief education officers, educators and students to obtain feedback on the proposed application. Initial results indicate that the proposed teacher evaluation system is innovative, and it has the potential to become an invaluable tool for educators who wish to maximize the impact of their lectures.

Due to the high number of injuries at crosswalks, the creation of smart applications is imperative to timely inform and protect citizens while crossing. The development of accurate applications first requires defining the factors that affect the safety of a pedestrian crossing. This paper presents a preliminary study on crosswalk safety as an effort to help develop automatic methods for assessing safety as well as Virtual Reality (VR) tools incorporating different danger scenarios in crosswalks. The study was based on a questionnaire where 101 regular pedestrian citizens answered various questions about crossing safety and then evaluated the safety of various crosswalks represented in a series of images. The results show that parked vehicles, the presence of obstacles, rubbish, damages, and holes on crosswalks play an important role in pedestrians' safety. In addition, a number of images used in the study were statistically evaluated by the participants as depicting unsafe crosswalks and can be used as examples when collecting data.

The term "Smart Classroom" has evolved over time and nowadays reflects the technological advancements incorporated in educational spaces. The rapid advances in technology, and the need to create more efficient and creative classes that support both in-class and remote activities, have led to the integration of Artificial Intelligence and smart technologies in smart classes. In this paper we discuss the concept of Artificial Intelligence in Education and present a literature review related to smart classroom technology, with an emphasis on emerging technologies such as AI-related technologies. As part of this survey key technologies related to smart classes used for effective class management that enhance the convenience of classroom environments, the use of different types of smart teaching aids during the educational process and the use of automated performance assessment technologies are presented. Apart from discussing a variety of technological accomplishments in each of the aforementioned areas, the role of AI is discussed, allowing the readers to comprehend the importance of AI in key technologies related to smart classes. Furthermore, through a SWOT analysis, the Strengths, Weaknesses, Opportunities, and Threats of adopting AI in smart classes are presented, while the future perspectives and challenges in utilizing AI-based techniques in smart classes are discussed. This survey targets educators and AI professionals so that the former get informed about the potential, and limitations of AI in education, while the latter can get inspiration from the challenges and peculiarities of educational AI-based systems.

VR-based training approaches can be used to empower the empathetic behavior of educators, raising their awareness and understanding of their learners, particularly in an era of social isolation and distancing. This paper presents research related to the use of VR as a tool for the practical training of educators aiming to empower their empathy skills through perspective-taking. Educator trainees participated in an experimental evaluation that involved exposure and interaction in a virtual classroom environment. Participants were divided into three groups; members of the first group experienced only the educator's perspective while members of the other two groups experienced both the educator's perspective and the perspective of students facing issues that may affect their academic performance and/or their integration in the school community. A thorough statistical analysis of the pre and post-experiment questionnaire responses, using ANOVA, indicated a significant impact of the VR intervention only for the two groups that experienced both the educator and student perspective. The results indicate the high added value of using VR with perspective-changing to strengthen empathetic behavior during the educator's training sessions.