During the CHI 2022 process, I was involved in the publications process as Publications Chair taking over from last year, with a more substantial role in developing and setting up the publication process. Moreover, and for the first time, I was engaged not only in the reviewing process as Associated Chair but this year as Subcommittee Co-Chair for the subcommittee “Interaction Beyond the Individual” with my Co-Chair Amanda Hughes, Brigham Young University. As a result, the planning for the conference and reviewing phase was intense so was the paper writing time. But also the personal outcome was a success with two papers, one of which received an honorable mention award.
VRception: Rapid Prototyping of Cross-Reality Systems in Virtual Reality
Cross-reality systems empower users to transition along the realityvirtuality continuum or collaborate with others experiencing different manifestations of it. However, prototyping these systems is challenging, as it requires sophisticated technical skills, time, and often expensive hardware. We present VRception, a concept and toolkit for quick and easy prototyping of cross-reality systems. By simulating all levels of the reality-virtuality continuum entirely in Virtual Reality, our concept overcomes the asynchronicity of realities, eliminating technical obstacles. Our VRception Toolkit leverages this concept to allow rapid prototyping of cross-reality systems and easy remixing of elements from all continuum levels. We replicated six cross-reality papers using our toolkit and presented them to their authors. Interviews with them revealed that our toolkit sufficiently replicates their core functionalities and allows quick iterations. Additionally, remote participants used our toolkit in pairs to collaboratively implement prototypes in about eight minutes that they would have otherwise expected to take days.
User Perceptions of Extraversion in Chatbots after Repeated Use
Whilst imbuing robots and voice assistants with personality has been found to positively impact user experience, little is known about user perceptions of personality in purely text-based chatbots. In a within-subjects study, we asked N=34 participants to interact with three chatbots with different levels of Extraversion (extraverted, average, introverted), each over the course of four days. We systematically varied the chatbots’ responses to manipulate Extraversion based on work in the psycholinguistics of human behaviour. Our results show that participants perceived the extraverted and average chatbots as such, whereas verbal cues transferred from human behaviour were insufficient to create an introverted chatbot. Whilst most participants preferred interacting with the extraverted chatbot, participants engaged significantly more with the introverted chatbot as indicated by the users’ average number of written words. We discuss implications for researchers and practitioners on how to design chatbot personalities that can adapt to user preferences.