Click on the title to browse this book

The visual representation of human-like entities in virtual worlds is becoming a very important aspect as virtual reality becomes more and more “social”. The visual representation of a character’s resemblance to a real person and the emotional response to it, as well as the expectations raised, have been a topic of discussion for several decades and have been debated by scientists from different disciplines. But as with any new technology, the findings may need to be reevaluated and adapted to new modalities. In this context, we make two contributions which may have implications for how avatars should be represented in social virtual reality applications. First, we determine how default and customized characters of current social virtual reality platforms appear in terms of human likeness, eeriness, and likability, and whether there is a clear resemblance to a given person. It can be concluded that the investigated platforms vary strongly in their representation of avatars. Common to all is that a clear resemblance does not exist. Second, we show that the uncanny valley effect is also present in head-mounted displays, but—compared to 2D monitors—even more pronounced.

This article analyses the state-of-the-art of virtual reality (VR) in higher education and provides an overview of the VR literature and identifies the need for the definition of key terms. Thus, it introduces three types of VR according to immersion level. Furthermore, analysis reveals a lack of systematic literature reviews (SLRs) on learning using immersive virtual reality (IVR). This article presents the results of the first SLR of the scientific literature on IVR in higher education indexed in Web of Science. A total of 291 articles were collected out of which 50 were selected for full-text analysis. We report three findings. First, we categorise and cluster the literature into formal aspects and research design and conclude that IVR research remains in its infancy. Furthermore, it lacks a sound and standardised research framework and design as well as comparative studies that are repeated for validation. Second, we analyse and discuss the current results and outcomes of the scientific research and identify the diversity of the reported research and learning outcomes with contradictory results, which are frequently due to specific and isolated scenarios. Third, this work is the first systematic scoping review on all studies from Web of Science that focuses on the use of IVR in higher education in general. We offer a unique overview of scientific articles on IVR in higher education without any limitation in time, scope or topic. Notably, the majority of the 50 articles do not present evidence-based and validated results; in particular, discussions and results related to pedagogical aspects are lacking.

The emergence of generative language models (GLMs), such as OpenAI’s ChatGPT, is changing the way we communicate with computers and has a major impact on the educational landscape. While GLMs have great potential to support education, their use is not unproblematic, as they suffer from hallucinations and misinformation. In this paper, we investigate how a very limited amount of domain-specific data, from lecture slides and transcripts, can be used to build knowledge-based and generative educational chatbots. We found that knowledge-based chatbots allow full control over the system’s response but lack the verbosity and flexibility of GLMs. The answers provided by GLMs are more trustworthy and offer greater flexibility, but their correctness cannot be guaranteed. Adapting GLMs to domain-specific data trades flexibility for correctness.

In the broader field of human behavior studies, there are several trade-offs for on-site experiments. To be tied to a specific location can limit both the availability and diversity of participants. However, current and future technological advances make it possible to replicate real-world scenarios in a virtual environment up to a certain level of detail. How these differences add up and affect the cross-media validity of findings remains a topic of debate. How a virtual world is accessed, through a computer screen or a head-mounted display, may have a significant impact. Not surprisingly, the literature has presented various comparisons. However, while previous research has compared the different devices for a specific research question, a systematic review is lacking. To fill this gap, we conducted this review. We identified 1083 articles in accordance with the PRISMA guidelines. Following screening, 56 articles remained and were compared for a qualitative synthesis to provide the reader a summary of current research on the differences between head-mounted displays (HMDs), computer screens, and the real world. Overall, the data show that virtual worlds presented in an HMD are more similar to real-world situations than to computer screens. This supports the thesis that HMDs are more suitable than computer screens for conducting experiments in the field of human behavioral studies.

With voice driven type design (VDTD), we introduce a novel concept to present written information in the digital age. While the shape of a single typographical character has been treated as an unchangeable property until today, we present an innovative method to adjust the shape of each single character according to particular acoustic features in the spoken reference. Thereby, we allow to keep some individuality and to gain additional value in written text which offers different applications - providing meta-information in subtitles and chats, supporting deaf and hearing impaired people, illustrating intonation and accentuation in books for language learners, giving hints how to sing - up to artistic expression. By conducting a user study we have demonstrated that - using our proposed approach - loudness, pitch and speed can be represented visually by changing the shape of each character. By complementing homogeneous type design with these parameters, the original intention and characteristics of the speaker (personal expression and intonation) are better supported.