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In this work, we further test the hypothesis that physical embodiment has a measurable effect on performance and impression of social interactions. Support for this hypothesis would suggest fundamental differences between virtual agents and robots from a social standpoint and would have significant implications for human-robot interaction. We have...
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... Physically-present robots are able to elicit more compliance [8], engage people more [10], exert greater influence [9], and engender more trust [32]. Similarly, researchers explicitly comparing physical robots with animated robot simulations have found that physical robots are perceived more positively [33], facilitate greater task performance [34], and are perceived as more anthropomorphic [35]. ...
Robots deployed into real-world task-based environments may need to provide assistance, troubleshooting, and on-the-fly instruction for human users. While previous work has considered how robots can provide this assistance while co-located with human teammates, it is unclear how robots might best support users once they are no longer co-located. We propose the use of Augmented Reality as a medium for conveying long-distance task guidance from humans' existing robot teammates, through Augmented Reality facilitated Robotic Guidance (ARRoG). Moreover, because there are multiple ways that a robot might project its identity through an Augmented Reality Head Mounted Display, we identify two candidate designs inspired by existing interaction patterns in the human-robot interaction (HRI) literature (re-embodiment-based and telepresence-based identity projection designs), present the results of a design workshop to explore how these designs might be most effectively implemented, and the results of a human-subject study intended to validate these designs.
... expected to provide students with high-quality education through face-to-face interactions [6,21,37,43]. Compared to video-displayed agents, physical robots can yield more compliance to their requests [6], elicit social behavior from learners beneficial to learning [22], be more engaging and enjoyable [26,27], and be perceived positively [31,36,45]. These findings suggest that robots can generate positive perceptions and improve task performance in educational situations because of their physical presence. ...
This study explores how much current mainstream Robot-Assisted Language Learning (RALL) systems produce outcomes compared to human tutors instructing a typical English conversation lesson. To this end, an experiment was conducted with 26 participants divided in RALL (14 participants) and human tutor (12 participants) groups. All participants took a pre-test on the first day, followed by 30 min of study per day for 7 days, and 3 post-tests on the last day. The test results indicated that the RALL group considerably improved lexical/grammatical error rates and fluency of speech compared to that for the human tutor group. The other characteristics, such as rhythm, pronunciation, complexity, and task achievement of speech did not indicate any differences between the groups. The results suggested that exercises with the RALL system enabled participants to commit the learned expressions to memory, whereas those with human tutors emphasized on communication with the participants. This study demonstrated the benefits of using RALL systems that can work well in lessons that human tutors find hard to teach.
... A robot can enhance an ITS by providing a social presence during the interaction. Compared to a screen system only, embodied robot tutors have been shown to cause greater compliance Bainbridge et al. (2011), higher learning gains Leyzberg et al. (2012), more engagement Wainer et al. (2007), and fewer mistakes Salomons et al. (2022b). A robot can also interact with the user as a peer or tutee rather than as the traditional teacher Salomons et al., 2022a;Chen et al., 2020. ...
Creating an accurate model of a user’s skills is an essential task for Intelligent Tutoring Systems (ITS) and robotic tutoring systems. This allows the system to provide personalized help based on the user’s knowledge state. Most user skill modeling systems have focused on simpler tasks such as arithmetic or multiple-choice questions, where the user’s model is only updated upon task completion. These tasks have a single correct answer and they generate an unambiguous observation of the user’s answer. This is not the case for more complex tasks such as programming or engineering tasks, where the user completing the task creates a succession of noisy user observations as they work on different parts of the task. We create an algorithm called Time-Dependant Bayesian Knowledge Tracing (TD-BKT) that tracks users’ skills throughout these more complex tasks. We show in simulation that it has a more accurate model of the user’s skills and, therefore, can select better teaching actions than previous algorithms. Lastly, we show that a robot can use TD-BKT to model a user and teach electronic circuit tasks to participants during a user study. Our results show that participants significantly improved their skills when modeled using TD-BKT.
... An indispensable property of robots in real-world environments is their physical embodiment [8]. The design of a robot's body has proved to affect various facets of HRI, such as how users experience, e.g., the social presence of robots [33,34], their levels of comfort and trust [35,36], empathy [37], attractiveness [38], and enjoyment [35,38]. Furthermore, utilizing soft materials in the design of social robot morphologies have been explored for intimate HRI [39], and it has been shown that the inclusion of soft materials increases perceived safety and comfort in close HRI [40]. ...
... An indispensable property of robots in real-world environments is their physical embodiment [8]. The design of a robot's body has proved to affect various facets of HRI, such as how users experience, e.g., the social presence of robots [33,34], their levels of comfort and trust [35,36], empathy [37], attractiveness [38], and enjoyment [35,38]. Furthermore, utilizing soft materials in the design of social robot morphologies have been explored for intimate HRI [39], and it has been shown that the inclusion of soft materials increases perceived safety and comfort in close HRI [40]. ...
The flexible bodies of soft robots provide exciting new possibilities for interaction with humans. In this paper, we propose a novel design paradigm, Soft Biomorphism, for soft robots centered on the idea of amplifying their inherent biomorphic aesthetic qualities and activating these as affordances for human interaction. Following this approach, we developed a set of biomorphic soft robotic prototypes and conducted two studies to understand the effects of biomorphic design aesthetics on people’s impressions of these prototypes. Based on qualitative data collected through five workshop sessions, the first exploratory study (n = 10) sought to investigate the envisioned uses and types of interactions that prototypes elicited within the context of personal robots. We found that various uses were considered and that most participants associated the biomorphic aesthetic design with soft robots contributing to emotional and physical well-being. Building on these results, we conducted a second study (n = 32) to investigate if soft robots with enhanced biomorphic qualities are perceived as more appealing and appropriate for physical human–robot interaction aimed at supporting well-being. We did not find any statistically significant preference for biomorphic soft robots. However, we found statistically significant differences in appeal ratings post-interaction for some prototypes, suggesting that physical interaction with soft robots can impact the perceived appeal. Based on our findings, we highlight key issues to bear in mind when considering biomorphic aesthetics in soft personal robot designs and provide tentative design recommendations to combine biomorphic and geometric elements and align visual appearance, tactility, and movement in future robot designs.
... Studies have already been conducted to investigate the relationship between physical embodiment level and human engagement, human perception of ECA [7], [3], [23], [24], and how well users perform certain tasks when interacting with agents of different embodiment levels [6], [5], [8]. However, there is a possibility that such results are due to novelty preference -the preference for new experienceswhich may have played an important role in these results. ...
... As early as 1986, Harwin, Ginige and Jackson proposed using robots for physical interaction in early education (Harwin et al., 1986). In addition, studies have shown that the presence of social robots can (1) help students achieve better task performance compared to virtual agents or robots displayed on screens (Leyzberg et al., 2012;Li, 2015) and (2) increase people's evaluation of robots and their interactions with robots by making robots appear more appealing, perceptive and enjoyable (Jung & Lee, 2004;Wainer et al., 2007). This advantage is likely attributable to many factors. ...
Along with the development of speech and language technologies and growing market interest, social robots have attracted more academic and commercial attention in recent decades. Their multimodal embodiment offers a broad range of possibilities, which have gained importance in the education sector. It has also led to a new technology-based field of language education: robot-assisted language learning (RALL). RALL has developed rapidly in second language learning, especially driven by the need to compensate for the shortage of first-language tutors. There are many implementation cases and studies of social robots, from early government-led attempts in Japan and South Korea to increasing research interests in Europe and worldwide. Compared with RALL used for English as a foreign language (EFL), however, there are fewer studies on applying RALL for teaching Chinese as a foreign language (CFL). One potential reason is that RALL is not well-known in the CFL field. This scope review paper attempts to fill this gap by addressing the balance between classroom implementation and research frontiers of social robots. The review first introduces the technical tool used in RALL, namely the social robot, at a high level. It then presents a historical overview of the real-life implementation of social robots in language classrooms in East Asia and Europe. It then provides a summary of the evaluation of RALL from the perspectives of L2 learners, teachers and technology developers. The overall goal of this paper is to gain insights into RALL’s potential and challenges and identify a rich set of open research questions for applying RALL to CFL. It is hoped that the review may inform interdisciplinary analysis and practice for scientific research and front-line teaching in future.
... This is problematic, since a robot presented in an image or video can be evaluated differently and might elicit a different behavior than a real robot (Li, 2015). Although researchers are aware of that loss of external validity (Bartneck, 2003;Wainer et al., 2007;Kiesler et al., 2008;Hoffmann et al., 2018), SB representations like pictures, videos or game-like scenarios are prevailing as test objects. ...
... All the above intuitively makes VR a suitable way to conduct experiments in HRI and some work has been done pursuing this intuition: Studies comparing VR and SB are suggestive of a general validity and usefulness of VR as a research method (Wainer et al., 2007;Kiesler et al., 2008;Liu et al., 2017;Whitney et al., 2020). Comparing feelings towards VR vs. real robots specifically, Inoue et al. (2005) found no significant differences, while Kamide et al. (2014) found that, although subjects did not show a different behavior, they reported different feelings towards the robot in VR compared to the one in the real world (RW). ...
... This interest is especially important when the robot's task is to convey information (Kidd and Breazeal, 2004). Studies observing that a real robot is perceived more entertaining (Wainer et al., 2007;Leite et al., 2008) and elicits more attention (Kennedy et al., 2015) than a SB-robot. According to Steinfeld et al. (2006) the VR environment offers more interaction possibilities than a SB environment, because the subject can get in contact with the robot with his virtual hands. ...
To reduce costs and effort, experiments in human-robot interaction can be carried out in Virtual Reality (VR) or in screen-based (SB) formats. However, it is not well examined whether robots are perceived and experienced in the same way in VR and SB as they are in the physical world. This study addresses this topic in a between-subjects experiment, measuring trust and engagement of an interaction with a mobile service robot in a museum scenario. Measures were made in three different settings, either the real world, in VR or in a game-like SB and then compared with an ANOVA. The results indicate, that neither trust nor engagement differ dependent on the experimental setting. The results imply that both VR and SB are eligible ways to explore the interaction with a mobile service robot, if some peculiarities of each medium are taken into account.
... This popular and practical interest, however, does not come without its drawbacks. A preliminary look into related academic literature reveals a fragmented structure, with research covering a wide range of topics, including human-robot and human-computer interactions (Ayache et al., 2022;Wainer et al., 2007), marketing and media (Aw et al., 2022), psychology and emotions (Horovitz, 2021), ethics and morality (Luxton and Hudlicka, 2021;Robinson, 2020) and so on. The diversity of these research streams naturally brings about a diversity of definitions of the virtual agent, which exists on a spectrum ranging from a digital user interface running on a simple algorithm (Beer et al., 2015), to a fully embodied anthropomorphised entity powered by AI (Alabed et al., 2022). ...
... Anthropomorphised virtual agents can convey a sense of social presence, bypassing the lack of interpersonal interaction (Verhagen et al., 2014), therefore making the "body" aspect of virtual agents a crucial dimension. However, it is the agent's physical presence, rather than its physical embodiment, that elicits more positive responses (Li, 2015;Wainer et al., 2007), adding another layer to the question of embodiment. Additionally, physical presence may or may not include animacy (defined as indicators of being alive, such as autonomous movement; Chiang et al., 2022). ...
... As we saw in the network analysis above, both verbal and non-verbal communication topics moved from being unconnected to the other topics, to highly connected and central to the current research domain. This evolution indicates their importance in aspects like emotions displayed by the agent (Chen et al., 2020;de Melo et al., 2010), embodiment (Wainer et al., 2007), and the movement of the agent (Kucherenko et al., 2021). Future research in this domain should continue to investigate various embodiment forms of the agent, from pure-product forms (e.g. ...
Virtual agent research has evolved into a substantial body of work, albeit one with a fragmented structure and overlapping, and at times inconsistent, definitions and results. The current paper presents a computational literature review of 1865 academic journal publications and conference proceedings from 1995 to 2022 using Latent Dirichlet Allocation to understand the publication trends in the field, its intellectual structure, and how topics within virtual agent research have evolved and relate to each other. Our results point to a model of 16 topics as best representing the current state of the research landscape. We present descriptions of these topics, as well as topic dynamics and networks, in order to provide a clear picture of the current state of the field. We then organise these topics into a Human-Virtual Agent Coexistence Framework, identifying current trends and opportunities for future research.
... Technologies have been investigated to address this bottleneck. Humanoid robots are being designed to promote healthy lifestyles [8] for older adults, such as serving as companions [9][10][11] and therapeutic/intervention tools [12][13][14][15][16]. Compared to a screen-based agent, users tend to enjoy spending time with robots and find the interaction helpful and useful [17], which may be due to the physical embodiment of the robot that enables a better social connection with users [18]. Literature reveals that the humanlike appearance of the robot to communicate, initiate interaction, and foster positive reactions to meet the personalized needs of users is essential to the acceptance and the efficacy of robot-mediated interventions for older adults [19,20]. ...
In this fast-aging society, many older adults fail to meet the required level of exercise due to trainer shortages. Therefore, we developed a robot tutor to investigate the feasibility of robot-mediated exercise for older adults. Twenty older adults participated in an experimental study. A pre-exercise survey was used to assess their background. Each participant experienced a 30-min robot-led Tai Chi exercise followed by a post-exercise survey to evaluate the easiness of following the robot and expectations for future robot design. Participants’ Tai Chi performances were evaluated in terms of completion and accuracy. Associations between the surveys and the performance were also analyzed. All participants completed the study. Fifteen out of the twenty subjects had at least one chronic condition, and most practiced Tai Chi before the study but had never interacted with a robot. On average, the participants scored 93.09 and 85.21 out of 100 for movement completion and accuracy, respectively. Their initial movement accuracy was correlated with their attitude towards exercise. Most subjects reported that they could follow the robot’s movements and speeches well and were interested in using a robot tutor in the community. The study demonstrated the initial feasibility of robot-led Tai Chi exercise for older adults.
... Much HRI research has already demonstrated differences in objective performance and subjective perception between purely virtual and purely physical robotic entities, demonstrating that embodied physical presence leads to greater influence [3], learning outcomes [43], task performance [51,89], gaze following from infants [56], proximity [3], exercise [25], positive perception [52], social facilitation [5], forgiveness [5], enjoyableness [25,68,88], helpfulness [25,69], and social attractiveness [25]. However, these works compared entirely physical and entirely virtual robot presence, without considering morphologies that blend the physical and the virtual, as enabled by AR technologies. ...
Augmented Reality (AR) technologies present an exciting new medium for human-robot interactions, enabling new opportunities for both implicit and explicit human-robot communication. For example, these technologies enable physically-limited robots to execute proven non-verbal interaction patterns such as deictic gestures despite not otherwise having the physical morphology necessary to do so. However, a wealth of HRI research has demonstrated that there are real benefits to physical embodiment (compared to, e.g., virtual robots on screens), suggesting AR augmentation of virtual robot parts could face similar challenges. In this work, we present empirical evidence comparing the use of virtual (AR) and physical arms to perform deictic gestures that identify virtual or physical referents. Our subjective and objective results demonstrate the success of mixed reality deictic gestures in overcoming these potential limitations, and their successful use regardless of differences in physicality between gesture and referent. These results help to motivate the further deployment of mixed reality robotic systems and provide nuanced insight into the role of mixed-reality technologies in HRI contexts.
