360° spaces are representations of real locations created using 360° images, enabling viewers to walk through by changing position. As basis for virtual field trips, they have proven to be valuable learning tools. In technological terms, 360° spaces are to be characterized as single-user applications. In contrast, Social VR applications are characterized by multi-user capability and user-specific avatars. From a learning perspective, the concepts of collaborative learning and embodiment have long been proposed as conducive to learning. Both concepts might be supported using Social VR. However, there is hardly any knowledge about the use of 360° spaces and Social VR. Accordingly, the research question arises how Social VR-based 360° spaces are perceived by learners. This article presents a mixed-method evaluation study (N = 16) – using a questionnaire and focus group discussions – of a 360° space based on the Social VR platform Mozilla Hubs used on PCs. The study highlighted the opportunities offered by Social VR-based 360° spaces but also revealed several challenges that need to be addressed to embrace the potential of Social VR-based 360° spaces to be utilized regularly in education. Accordingly, the study represents relevant preparatory work for the use of multi-user 360° spaces in playful learning environments, such as educational escape rooms.

Digital learning environments exhibiting spatial dimensions, such as VR experiences or virtual labs, have become increasingly common in recent years. At the same time, it is known that gamification, i.e., the application of game-like mechanisms, might support the motivational design of learning environments. However, so far, there seems to be no systematic overview on whether and how spatial dimensions are incorporated into gamification mechanisms. Accordingly, we conducted a systematic literature review to identify gamification mechanisms that use spatial dimensions. Out of 849 articles we finally included 11 articles found in the three databases ScienceDirect, IEEE, and ACM DL that conducted gamification in the context of spatial digital learning environments. For the most part, the gamification mechanisms used in these 11 articles did not relate to any spatial dimension. Conclusively, we state that there have been few approaches to gamification exploiting the spatial dimension. Given the limited findings in the literature, we propose developing a model to bridge existing gaps and support a structured approach to incorporating spatial dimensions into gamification mechanisms. Accordingly, we contribute to enhancing spatial digital learning environments with further motivational cues through spatial gamification mechanics.

The integration of artificial intelligence (AI) into the manufacturing sector introduces new challenges and demands for the engineering workforce in the evolving European economy. This paper investigates how advancements in AI tools, especially in manufacturing, necessitate a shift in engineering education to equip graduates with relevant skills and ethical understanding. While AI is not new to manufacturing, its ongoing development and increased accessibility bring forth fresh challenges related to required competencies and ethical considerations. Furthermore, this work explores the potential of incorporating recent AI tools, such as ChatGPT and other generative adversarial networks, into engineering education. This is illustrated through a case study of a master’s level digitalization course. In this course, AI tools aimed to help students bridge their programming knowledge gaps and educate them on ethical AI use, providing a model adaptable to lifelong learning courses in the field. This inquiry also addresses the broader concerns related to AI misuse in academic settings and the subsequent difficulties in plagiarism detection and accurate learning outcome assessment. The discussion does not argue against AI adoption but emphasizes managing its inadvertent impacts on the industry and society. By integrating emerging technologies and their ethical use into the curriculum, the engineering education system can better align with the shifting demands of the workforce in an increasingly digitalized manufacturing landscape.

The concept of the industrial metaverse represents a revolutionary fusion of digital and physical realms within the industrial sector. This paper delves into the intersection of the internet of things (IoT) and the metaverse, aiming to define its emerging landscape through an analysis of current literature and identification of future research directions. Employing a combination of quantitative and qualitative methods, including bibliometric analysis and the Visualization of Similarities (VOS) technique, our study maps the field of the industrial metaverse. The PRISMA method, which we used for our contribution, provides a systematic approach to our research process, and provides a base for the sequent thematic analysis, where a thesaurus is used to account for keyword variations, enriching our understanding of the metaverse's potential in industrial applications. We argue that the industrial metaverse is not merely a technological advancement but opens the way in which industries operate, collaborate, and innovate. This paper aims to establish a foundational framework for future research and development in the industrial metaverse, offering a clear and precise overview about the current state of research on the metaverse and internet of things.

This paper explores the development of digital systems to identify and reduce cognitive stresses in contemporary manufacturing environments with increasing numbers of robots and smart machines. To achieve this, the study attempts to answer the following research question: How can technology-driven advancements in engineering psychology be leveraged to foster more productive, ethical, and psychologically supportive collaboration between humans and robots in the context of modern manufacturing environments? The study explores relevant literature to gain deeper insights into the subject succeeded by the development of a prototype composed of two digital solutions. By improving cognitive ergonomics through the detection and recognition of non-verbal cues, as well as reducing cognitive stress by providing real-time information on the positions of mobile robots, this study offers potential solutions to the social and psychological challenges of human-robot collaboration. The paper concludes with an analysis of the final prototype, a discussion on sustainability implications, and recommendations for future research. Overall, this research aims to bridge the gap between human workers and technology in the manufacturing sector, facilitating a harmonious and productive collaboration that aligns with the goals of Industry 5.0.

A key motivation to adopt data-driven solutions in facility-internal logistic systems is to create more responsive, efficient, and sustainable systems through a seamless data flow. There is thus a need to analyse the logistics system’s requirements from a data efficiency perspective. This paper presents and demonstrates a novel method, based on established literature, to assure that a transition to data-driven internal logistics leads to improvements in operational performance objectives. First, we identify wastes on the shopfloor caused by inefficient data flows. Second, we portray the trajectories of managerial capacities enhancements, supporting decision makers toward a to-be scenario. Two case studies are presented where the method has been implemented and used for demonstration and validation purposes. The results show that the method is beneficial in a waste-elimination and continuous improvement setting, linking improvements, detected wastes, enabling technologies, and managerial capacities in terms of monitoring, control, optimization, and autonomy.

Interactive learning espouses a “hands-on” approach, aiming to foster student engagement. In an interactive form of learning, serious games, and gamification have been used in the classrooms to engage students. Nowadays, many serious games and gamification with AR are used in classrooms as it encourages engagement in interactive learning. However, with the usage of such technologies, it remains challenging to engage students with certain impairments as the tools are not designed to accommodate the needs of students with certain impairments. In this poster paper, the focus is on challenges related to red-green color blindness, since this is regularly affecting the learning experience among our students. Making learning content accessible in an AR environment depending on the type and severity of this color blindness is challenging and requires a better understanding of the specific requirements in designing AR in serious games and gamification for red-green colorblindness. To accomplish this, a systematic literature review (SLR) is conducted with the aim of highlighting the existing challenges in designing AR: i) serious games and ii) gamification. The paper also examines the challenges of using AR in interactive learning in a broader context and identified challenges with the key findings discussed.

Recent technological advances in capturing real-time and large amounts of data provide an opportunity for production logistics systems to enhance their performance. Transitioning to a data-driven system is a complex and multifaceted process. While many articles highlight the benefits of data-driven applications, there are few empirical studies on how production logistics are influenced at the system level. This paper examines the potential benefits of transitioning to a data-driven production logistics system through two case studies. The first case involves an internal material flow between two departments in a large Swedish heavy automotive manufacturer with complex multi-product internal logistic flows. The second case involves the cross-docking flow of pallets in one terminal of a major courier industry player in the Nordic region with diverse customers. The current situation in each case was compared to a smart data-driven state through discrete event simulation, expert interviews, observations, and document review. The analysis shows that a seamless data flow can improve the overall performance of the systems in terms of lead-time, resource utilization efficiency, responsiveness, and space efficiency. The study provides insights towards creating a roadmap for the transition to a data-driven production logistics system.