Harassment and personal space invasions have been a core privacy threat in social virtual worlds from the outset, often causing lasting harm to victims and reducing their willingness to engage with these technologies. Media coverage of such incidents further amplifies fear and discourages potential users. In response, platforms have increasingly emphasized proximity-control features that allow users to protect themselves both preventively and reactively – most prominently through safety bubbles and avatar blocking. However, no study to date has examined whether these features influence adoption-relevant factors. To address this gap, we conducted a video vignette-based online survey with 195 participants in Germany, each exposed to a mild personal space invasion scenario under one of three conditions: no safety features, safety bubble, or avatar blocking. Results show that both safety bubbles and avatar blocking positively influence relevant adoption factors such as trust, controllability, satisfaction, and use intention. Safety bubbles additionally improved perceived safety and reliability, appearing to be the more effective solution due to their preventive nature. Finally, implications of the findings are discussed.

Following the Quantified Self (QS) movement, sports apps increasingly adopt self-tracking technologies that offer data-driven insights into personal competencies to enhance self-efficacy. However, sustained engagement with QS technology remains challenging, as interpreting data is complex. One potential solution is to make QS data more meaningful to users. To address this, we present a player card feature within a QS sports app, incorporating a personalized avatar to enhance users’ enjoyment, data meaningfulness, and self-efficacy to promote continued use. We evaluate the app through a field experiment in a soccer context to examine the impact of the avatar feature. Results indicate that avatar identification positively affects self-efficacy, data meaningfulness, continued use intention, and enjoyment, though enjoyment did not impact continued use. Our findings suggest that (1) avatar identification can be enhanced through personalization, (2) personalized avatars effectively boost self-efficacy, and (3) sustained engagement may rely more on meaning than on enjoyment alone.

Highlights• We actively trigger people’s tendency to treat robots as human-like social actors• Two sociopsychological mechanisms are applied in an industrial use case• Perspective-taking fosters cognitive trust in cobots• Anthropomorphism increases emotional distrust of participants• Human-like cobot designs may prevent collaboration instead of fostering it

While gaming increasingly permeates many facets of our daily lives, it is also gaining relevance as an in-car experience. However, despite the growing interest in in-car gaming within both research and practice, we lack a structured understanding of the phenomenon's main research fields and prevailing characteristics. Thus, this paper presents the findings of a scoping review of 42 relevant papers on gaming in cars. We identified five emerging research substreams: in-car game prototypes, gaming during automated driving, theoretical considerations for in-car gaming, effects of gaming while driving, and technology enabling in-car gaming. Furthermore, we provide an overview of the research's major characteristics about the game, gaming device, vehicle, and user. We reflect on trends recognized in our review, discuss contradictory results, for instance, regarding safety, and question whether a unique in-car gaming experience may exist. We propose research questions based on identified trends and gaps to guide future HCI research in this field.

Achieving cooperation between individuals is challenging and often driven by self-beneficial motives. On the other hand, people also seem capable of subordinating their personal interests and of engaging in cooperation for motives other than their own, i.e. out of altruistic impulses. One context in which both motivational facets can be observed is multiplayer online games. However, there is a lack of knowledge about how cooperation based on altruism and egoism develops in games, which also prevents us from transferring this knowledge as a form of gamification. In this study, we explore which game features are accountable for altruistic and egoistic sentiment, and how these distinctive demeanours induce cooperation in games, with the intent to also derive implications for gamification. We employ we-intention and I-intention theory and conduct a survey among players of the game Ingress (N = 206). Our findings imply that (1) cooperative game design can give rise to within-group altruism in form of enjoyment in helping others and cooperative goals, (2) altruism can lead to the formation of we-intentions, and (3) individualistic game features invoke I-intentions and self-centered motivations in games in the form of recognition-seeking. Theoretical and practical implications are provided for cooperative game and gamification design.

Gamification has become one of the main areas in information systems and human–computer interaction research related to users’ motivations and behaviors. Within this context, a significant research gap is the lack of understanding of how users’ characteristics, especially in terms of their preferences for gameful interaction (i.e., user typologies), moderate the effects of gamification and, furthermore, how gamification could be tailored to individual needs. Despite their prominence in classifying users, current typologies and their use in research and practice have received severe criticism regarding validity and reliability, as well as the application and interpretation of their results. Therefore, it is essential to reconsider the relationships and foundations of common user typologies and establish a sound empirical basis to critically discuss their value and limits for personalized gamification. To address this research gap, this study investigated the psychometric properties of the most popular player types within tailored gamification literature (i.e., Bartle’s player types, Yee’s motivations to play, BrainHex, and HEXAD) through a survey study (n=877) using their respective measurement instruments, followed by a correlation analysis to understand their empirical relations and an exploratory factor analysis to identify the underlying factors. The results confirm that user typologies, despite their different origins, show considerable overlap, some being consistent whereas others contradicted theoretically assumed relationships. Furthermore, we show that these four user typologies overall factor into five underlying and fundamental dimensions of Socialization, Escapism, Achievement, Reward Pursuit, and Independence, which could be considered common concepts that may essentially reflect key determinants of user motivation in gamification. Our findings imply that future research and practice in tailored gamification design should shift the focus from developing and applying ever more nuanced typologies to understanding and measuring the key underlying determinants of user motivation in gameful systems. Moreover, given the considerable interrelationships between these determinants, we also argue that researchers should favor continuous representations of users’ motivations in specific situations instead of a dichotomous operationalization of user types as static manifestations of their preferences.

The recent progress in generative AI models, particularly large language models (LLMs), has brought about a transformation in the field of education. Conversational LLM services, such as Google's Bard and OpenAI's ChatGPT, offer students access to many abilities such as summarization and generation of text and code, and on-demand replies to questions on expert topics. In this paper, we observe ChatGPT to explore how LLM services impact learning and instruction in higher education. First, we mapped the capabilities of the system by reviewing the grey literature on ChatGPT and using the system ourselves for two months. Second, we selected a Bachelor level computer science curriculum from a Finnish university, and examined the impact of ChatGPT on the offered courses. As an outcome of this study, we highlight 13 implications for students' learning in higher education, and discuss the contemporary future of AI-assisted learning in universities and beyond.

Digital companions and social robots empowered to have social capabilities by artificial intelligence (AI) are increasingly finding their way into our everyday lives. Even though these technologies benefit individuals seeking companionship and social interaction, adopting AI-powered social robots and companions remains a challenge. There is little known about effective approaches to overcoming barriers between humans and such systems that prevent their acceptance in the field. By applying the approach of perspective switching, we are examining whether taking the perspective of an AI-powered social robot can improve users’ perceptions of social robots and increase relevant antecedents of technology acceptance. Our study demonstrates that instruction-based perspective switching is a promising approach to influence the perceived usefulness, perceived enjoyment, and perceived sociability towards an AI-powered social robot and thus proves to be a useful means to support robot acceptance in society.

Organizations deploy gamification in CSCW systems to enhance motivation and behavioral outcomes of users. However, gamification approaches often cause competition between users, which might be inappropriate for working environments that seek cooperation. Drawing on the social interdependence theory, this paper provides a classification for gamification features and insights about the design of cooperative gamification. Using the example of an innova-tion community of a German engineering company, we present the design of a cooperative gamification approach and results from a first experimental evaluation. The findings indicate that the developed gamification approach has positive effects on perceived enjoyment and the intention towards knowledge sharing in the considered innovation community. Besides our conceptual contribu-tion, our findings suggest that cooperative gamification may be beneficial for cooperative working environments and represents a promising field for future research.