Virtual Reality (VR) is gaining popularity and is increasingly adopted across various industries for its potential to deliver immersive and effective skill development. However, we observe that VR training often follows a one-size-fits-all approach. Trainings typically do not adapt to to individual skill levels, which is particularly important in industrial assembly, where user profiles and expertise levels vary widely. To address this, we applied the concept of adaptive learning to VR assembly training, enabling the system to dynamically provide assistance levels when users struggle and gradually reduce support as their proficiency increases. This paper investigates the learning performance and subjective impact of two types of such adaptive approaches and a non-adaptive variant in a VR user study with 36 participants. The results show that adaptive training significantly enhances user experience and reduces perceived workload. At the same time, adaptive VR learning is found to have a positive impact on learning performance (quantified as a reduced number of assembly mistakes after training). In summary, our findings underscore the potential of applying adaptive learning approaches in VR. To guide future research, we propose guidelines to support the practical adoption of adaptive learning in VR training in manufacturing and beyond.

In recent years, the integration of Artificial Intelligence (AI) has sparked revolutionary progress across diverse domains, with sports applications being no exception. At the same time, using real-world data sources, such as GPS, weather, and traffic data, offers opportunities to improve the overall user engagement and effectiveness of such applications. Despite the substantial advancements, including proven success in mobile applications, there remains an untapped potential in leveraging these technologies to boost motivation and enhance social group dynamics in Virtual Reality (VR) sports solutions. Our innovative approach focuses on harnessing the power of AI and real-world data to facilitate the design of such VR systems. To validate our methodology, we conducted an exploratory study involving 18 participants, evaluating our approach within the context of indoor VR cycling. By incorporating GPX files and omnidirectional video (real-world data), we recreated a lifelike cycling environment in which users can compete with simulated cyclists navigating a chosen (real-world) route. Considering the user’s performance and interactions with other cyclists, our system employs AI-driven natural language processing tools to generate encouraging and competitive messages automatically. The outcome of our study reveals a positive impact on motivation, competition dynamics, and the perceived sense of group dynamics when using real performance data alongside automatically generated motivational messages. This underscores the potential of AI-driven enhancements in user interfaces to not only optimize performance but also foster a more engaging and supportive sports environment.

Operators’ well-being is a key factor for the success of industrial production processes. Even though research has studied the well-being aspects of the industry, such as support and improvement of ergonomics, there is still a long way to go to achieve a sustainable and healthy work context for manufacturing industry. We believe the Human-Computer Interaction community can contribute by developing research on worker well-being in real-life settings. This workshop intends to offer a venue for HCI researchers that focus on worker well-being for the manufacturing industry and other industry domains.

This paper demystifies listeners’ wishes with respect to broadcast radio innovation (with a specific focus on radio-mediated music consumption). Our study encompasses an ideation workshop with radio experts, an exploratory survey and a mixed methods empirical evaluation. The empirical evaluation uses two concrete concepts (i.e., letting listeners on-the-fly replace radio content with preferred content and fostering participatory radio production by involving listeners as radio content curators) as a lens to zoom in on the questionable desirability of radio innovation. It is learned that a significant consumer group exists who will stay loyal to broadcast radio even if it does not evolve substantially, whereas others need disruptive incentives to start listening to radio (again). From our results we distill design recommendations to educate the radio production community about how best to approach radio innovation.

People with Multiple Sclerosis (pwMS) suffer from a diverse set of symptoms such as fatigue, pain, depression, and decline in motor and cognitive function. It has been proven that physical activity has a positive effect on most of these symptoms. However, many pwMS lead sedentary lives, and do not meet the guidelines for physical activity. We propose WalkWithMe, a mobile application that supports pwMS in walking. WalkWithMe coaches pwMS in achieving a personal goal over a period of 10 weeks. We conducted a workshop with pwMS and brainstorm sessions with experts in rehabilitation to define the design choices of WalkWithMe. We examined the impact of WalkWithMe in a 10-week field study with 13 pwMS. The study revealed insights in walking habits, and positive trends in walking capacity. In this paper, we present the design aspects of WalkWithMe, findings of our 10-week evaluation, and resulting insights on goal setting for pwMS.

Persons that suffered from a cardiac disease are often recommended to integrate a sufficient level of physical exercise in their daily life. Initially, cardiac rehabilitation takes place in a closely monitored setting in a hospital or a rehabilitation center. Sustaining the effort once the patient has left the ambulatory, supervised environment is a challenge, and drop-out rates are high. Emerging approaches such as telemonitoring and telerehabilitation have been proven to show the potential to support the cardiac patient in adhering to the advised physical exercise. However, most telerehabilitation solutions only support a limited range of physical exercise, such as step-counting during walking. We propose BoB (Back on Bike), a mobile application that guides cardiac patients while cycling. Design choices are explained according to three pillars: ease of use, reduce fear, and direct and indirect motivation. In this paper, we report the results from a field study with cardiac patients.