Linguistic conventions that arise in dialogue reflect common ground and can increase communicative efficiency. Social robots that can understand these conventions and the process by which they arise have the potential to become efficient communication partners. Nevertheless, it is unclear how robots can engage in convention formation when presented with both familiar and new information. We introduce an adaptable game platform, SPOTTER, to study the dynamics of convention formation for visually grounded referring expressions in both human-human and human-robot interaction. Specifically, we seek to elicit convention forming for members of an inner circle of well-known individuals in the common ground, as opposed to individuals from an outer circle, who are unfamiliar. We release an initial corpus of 5000 utterances from two exploratory pilot experiments in Dutch. Different from previous work focussing on human-human interaction, we find that referring expressions for both familiar and unfamiliar individuals maintain their length throughout human-robot interaction. Stable conventions are formed, although these conventions can be impacted by distracting outer circle individuals. With our distinction between familiar and unfamiliar, we create a contrastive operationalization of common ground, which aids research into convention formation.

This study addresses the question to which extent individual online self-presentations become more similar globally, due globalisation and digitalisation, or whether ethno-racial identity predisposes individuals’ online self-presentation. That is, we examined the degree to which individuals varying in ethno-racial identity converge or diverge in online self-presentation. A large-scale content analysis was conducted by collecting selfies on Instagram (i.e. #selfietime; N = 3881). Using facial recognition software, selfies were allotted into a specific ethno-racial identity based on race/ethnicity-related appearance features (e.g. Asian, Black, Hispanic, and White identity) as a proxy for externally imposed ethno-racial identity. Results provided some evidence for convergence in online self-construction among selfie-takers, but generally revealed that self-presentations diverge as a function of ethno-racial identity. That is, results showed more convergence between ethno-racial identity for portraying selfies with objectified elements, whereas divergence in online self-presentations occurred for portraying contextualised selves and filter usage. In all, this study examined the complexity of online self-presentation. Here, we extend earlier cross-cultural research by exploring the convergence-divergence paradigm for the role of externally imposed ethno-racial identity in online self-presentation. Findings imply that ethno-racial identity characteristics remain important in manifestations of online self-presentations.

Research has shown that social robots carry potential to be used in an educational setting. The possibility to have multiple roles carried out by one tool does not only instigate curiosity but also raises concerns. Whereas practical challenges get tackled by rapid technological advances, the moral challenges often get overlooked. In this study, we examined the moral values related to educational robots from a teachers' perspective, by first identifying concerns and opportunities, and subsequently linking them to (moral) values. We conducted focus group sessions with teachers to explore their perceptions regarding concerns and opportunities related to educational robots. Teachers voiced several considerations ranging from having concerns towards privacy to seeing opportunities in adding friendship and attachment a robot could emanate.

Social robots are increasingly studied and applied in the educational domain. Although they hold great potential for education, they also bring new moral challenges. In this study, we explored the moral considerations related to social robots from the perspective of Dutch educational policymakers by first identifying opportunities and concerns and then mapping them onto (moral) values from the literature. To explore their moral considerations, we conducted focus group sessions with Dutch Educational Policymakers (N = 20). Considerations varied from the potential to lower the workload of teachers, to concerns related to the increased influence of commercial enterprises on the educational system. In total, the considerations of the policymakers related to 15 theoretical values. We identified the moral considerations of educational policymakers to gain a better understanding of a governmental attitude towards the use of social robots. This helps to create the necessary moral guidelines towards a responsible implementation of social robots in education.

We investigated the effects of facial similarity between users and embodied agents under different experimental conditions. Sixty-four undergraduates interacted with two different embodied agents: in one case the agent was designed to look somewhat similar to the user, and in the other case the agent was designed to look dissimilar. We varied between subjects how helpful the agent was for a given task. Results showed that the facial similarity manipulation sometimes affected participants' responses, even though they did not consciously detect the similarity. Specifically, when the agent was helpful, facial similarity increased participantsi ratings of involvement. However, when exposed to unhelpful agents, male participants had negative responses to the similar-looking agent compared to the dissimilar one. These results suggest that using facially similar embodied agents has a potential large downside if that embodied agent is perceived to be unhelpful.

Abstract This paper presents an empirically tested theoretical framework to explain user engagement and end‐user satisfaction with interactive agents. Such a framework is not only important from a scientific point of view; application designers may find a set of dos and don'ts that help them create more satisfying embodied agents in different task domains and social settings. From a multidisciplinary perspective, we have conducted a series of experiments to verify underlying mechanisms in the processes of interacting and engaging with embodied agents in various task domains. Our results show that the most commonly held views are not always tenable; sometimes other factors provide better explanations for liking an embodied agent or end‐user satisfaction. For example, it is not realism but rather affordances and ethics that are key for understanding user responses, and a beautiful design is not always the most preferable. From our results, guidelines for designers and future research are reflected upon. Copyright © 2009 John Wiley & Sons, Ltd.

Human-like characters in the interface may evoke social responses in users, and literature suggests that realism is the most important factor herein. However, the effects of interface characters on the user are not well understood. We developed an integrative framework, called I-PEFiC, to explain ‘persona’ and realism effects on the user. We tested an important part of the model using an experimental design in which 140 middle school students were class-wise shown an informative virtual reality demonstration that incorporated either a realistic or an unrealistic (fantasy) interface character, or no character. Findings show, first, no persona effect on task performance. We discuss how user engagement might be related to persona effects. Second, designed realism of the interface character contributed to user engagement when controlled for various user perceptions. Moreover, perceived aesthetics and task-relevance further influenced user engagement. Third, user engagement and task performance combined better predicted satisfaction than either one of the factors alone. In sum, several appearance- and task-related factors contributed to user engagement and user satisfaction. Thus, realism is not all.