A child’s bedroom holds the potential to be a meaningful space that scaffolds both practical and emotional needs. While home IoT technologies offer unique opportunities to enhance the room’s meaning, studies show children tend to associate them with practical rather than emotional use-cases. We present programmable IoT prototypes designed to overcome this tendency by applying two design principles: (1) Encourage self-appropriation and meaning-making using an open-ended design, simple coding blocks, and abstract outputs; (2) Encourage emotional use-cases using an explicit affordance. In a qualitative study, children used the prototypes in their bedrooms, appropriating them by coding personal use-cases that were both practical and emotional. We conclude that if designed appropriately, children can leverage IoT prototypes to enhance the meaning of their bedroom.

Deliberate regulation of diaphragmatic breathing can contribute to well-being. We present a targeted-heat wearable designed to direct attention inward during breathing practice. In a mixed-methods study, breathing was guided with a pulsing-heat or a screen-based app. We included physiological measures of heart-rate, HRV, and breathing pace; self-report questionnaires on interoception and mindfulness; and qualitative interviews. Results show both groups adhered well to the breathing guidance, yet heat-condition participants reached lower heart-rate and reduced sympathetic activation, physiological markers associated with stress reduction. They also reported higher interoceptive awareness, specifically self-regulation and body-listening abilities, alongside significantly higher state mindfulness. Qualitative findings revealed that targeted-heat fostered a stronger connection with bodily sensations and emotions, while visual feedback was often experienced as pulling attention outward. Our work suggests that breathing with the heat wearable increases the known positive outcomes of diaphragmatic breathing, helping people connect more deeply with their bodies by directing attention inward.

It is well established that when people seek medical care for physical conditions, their affective state significantly impacts health and recovery. Despite this, patients’ emotional needs are often overlooked due to the prioritization of physical care and resource constraints. Robots’ social capabilities, especially robotic attentiveness, present an opportunity to address this gap and enhance patients’ experience in healthcare settings. While robots are already integrated into healthcare, they are largely leveraged for functional support, with limited attention to their potential role in addressing affective challenges. In this field study, we evaluated whether a simple attentive robot could improve the affective experience in the emergency department (ED) of a public general hospital. Participants’ waiting experience was compared across three conditions: (1) waiting next to an attentive robot; (2) waiting next to a non-attentive robot; and (3) waiting without a robot. Behavioral and self-report measures indicated that the attentive robotic behavior reduced the unpleasantness of the waiting experience. Our findings highlight the power of leveraging simple robotic attentiveness to support patients' affective state in stressful healthcare environments.

Cognitive trust, the belief that a robot can accurately perform tasks, is crucial for effective human-robot interaction. While robot competence and reliability are known to build this trust, recent research shows that affective factors like attentiveness also matter. This study examines how competence and attentiveness interact to shape cognitive trust, specifically testing whether one factor can compensate for the other. Participants completed a search task with a robotic dog in a 2 × 2 design varying competence (high/low) and attentiveness (high/low). Results showed that high attentiveness compensates for low competence: participants working with an attentive but poorly performing robot reported trust levels similar to those working with highly competent robot. These findings suggest that building cognitive trust involves emotional processes often overlooked in traditional competence-based models.

Animacy is central to HRI, as it is critical for perceptions of intentionality and influences acceptance, interaction quality, and trust. In order to better understand the underlying mechanisms of the sense of animacy and its role in HRI, we conducted an experiment (n=13) using a social robotic object that is ambiguous with respect to its perceived animacy. We examined how brain activity related to a subjective animacy rating of the robot by participants after watching it perform simple gestures. Using functional imaging, we found that the ventral occipitotemporal (VOT) cortex, a region known to distinguish animate from inanimate entities, also responds to robots along this same organizational gradient. In an exploratory analysis, activity in the left VOT was associated with the individual differences in participants’ subjective animacy rating of the robot. This extends established principles of animacy perception to non-humanoid robots and suggests that individual differences in brain responses may shape how robots are experienced. We discuss implications for HRI, including guiding social cue design, informing gesture alignment with robot roles, and raising ethical considerations around attachment and trust.

We introduce a novel approach to evaluate how the design properties of morphing metamaterial influence shape-changing experiences. We leverage parametric design to create cutting patterns that change the Density and Geometry material properties. Using laser-cutting, we apply the patterns to a non-stretchable woven textile, resulting in a stretchable metamaterial that we actuate using an electromagnetic coil. This systematic design approach leads to programmatic control over the material movement, making it suitable for controlled evaluation of perceived experience. In a 2×2 mixed-method study, we assess how the metamaterial’s Density and Geometry properties impact the observed experience. Our findings indicate that such changes significantly and independently affect participants’ perceived emotions, mood, associations, and preferences. Our research contributes to the body of work of systematic studies in the shape-changing community. By using our morphing metamaterial design and implementation technique, coupled with our controlled evaluation of specific design properties, we have revealed new insights about the influencing factors of shape-changing experiences. We have incorporated these insights into our morphing metamaterial design guidelines, which outline the impact of Density and Geometry properties on an observer’s perceived emotions. We hope our work will open up new possibilities for expressive, evocative metamaterial-focused shape-changing experiences.

Emergent leadership in teams is known as a special type of informal leadership that has unique benefits. Given that this form of leadership can be developed only organically from within the team, an informal leader may not emerge and the associated advantages can be missed. We explored the possibility of leveraging robotic social behavior to facilitate the emergence of leadership in a team. We evaluated whether a robot displaying explicit peer liking towards a specific team member would encourage that team member to take the lead. Two (stranger) participants were asked to engage in a search task together with a robotic dog who either presented peer-liking behavior toward one or both of them during the opening encounter. Our findings suggest that the robot's peer liking led the “Liked” participant to report higher sense of leadership and higher sense of responsibility over the task. Behavioral measures also indicated that the “Liked” participant managed the team's performance. We suggest that integrating a robot into human teams presents an opportunity to facilitate unique dynamics that would not develop when imposing a structure on the team from the outside.

Cognitive and affective trust are fundamental elements in human-robot interactions. Previous research suggests that robots' affective behaviors related to affective trust can also impact cognitive trust. In this work, we explored whether the opposite influence also exists and whether robots' cognitive behaviors related to cognitive trust can also impact affective trust. Our results revealed that the robot's cognitive capabilities significantly impacted cognitive trust but did not influence affective trust. Participants in the High Competence Robot condition reported higher cognitive trust scores and were more likely to trust the robot's suggestions compared to the Low Competence Robot and Baseline conditions. We did not observe any differences in affective trust, and almost all participants in all conditions reported low affective trust. We suggest that while robot cognitive performance can effectively build cognitive trust, comprehensive trust development may require affective-related behaviors.

As multi-robot environments become more common, it is important to assess the robots' impact on the humans interacting with them and its magnitude. We investigated whether an interaction with two simple non-humanoid robots can be perceived as an intentional collusion aimed to deceive the person interacting with them. We evaluated if such a negative interaction would result in shaping people's perception of the robots in the interaction and extend to shaping their attitudes towards robots in general. In the study, participants played a gambling game with two simple non-humanoid robots: a “Dealer” responsible for card shuffling and an “Advisor” providing recommendations. We tested participants' experience when the “Advisor” robot gave a false recommendation in the final round, causing them to lose all their winnings. Our findings indicated that this single instance of perceived deception led to a negative perception of the “Advisor” robot, and also negatively influenced people's attitudes toward robots in general, at least temporarily. This study highlights the importance of carefully designing interactions in multi-robot environments, even when the interaction involves very simple robots. Careful consideration of ingroup-outgroup effects and verifying that the robots' collaboration is not interpreted as intentional deception is essential for avoiding powerful negative effects that reach beyond the specific interaction with the robots.

As robots become common in our everyday lives, their presence can impact how we view ourselves due to humans' inherent tendency for social comparison. This study explored how performing a simple search task alongside a robot can influence self-esteem and self-efficacy. These basic psychological constructs are known to contribute strongly to human well-being. Participants were asked to look for specific target symbols printed on cubes, while a robot performed a similar independent task next to them. They were assigned to one of three conditions: Upward comparison, where the robot's performance was perceived as superior; Downward comparison, where the robot's performance was perceived as inferior; or Equal performance, where the robot's performance was equal to their performance. While there was no direct interaction with the robot, performing a task next to it led participants to automatically engage in social comparison and compare their performance and capabilities to those of the robot. Our findings reveal that participants in the Upward comparison condition experienced a decrease in self-esteem, self-efficacy, and performance accuracy compared to the Downward comparison and Equal performance. The results suggest that even without direct interaction, simply performing a task alongside a robot can significantly impact individuals' basic psychological constructs and the way they perceive themselves. As robots increasingly share environments with humans, this study highlights the importance of considering people's tendency for social comparison when designing human-robot interaction and the extent of its impact on humans' well-being.

Robots come in various forms and have different characteristics that may shape the interaction with them. In human-human interactions, height is a characteristic that shapes human dynamics, with taller people typically perceived as more persuasive. In this work, we aspired to evaluate if the same impact replicates in a human-robot interaction and specifically with a highly non-humanoid robotic object. The robot was designed with modules that could be easily added or removed, allowing us to change its height without altering other design features. To test the impact of the robot’s height, we evaluated participants’ compliance with its request to volunteer to perform a tedious task. In the experiment, participants performed a cognitive task on a computer, which was framed as the main experiment. When done, they were informed that the experiment was completed. While waiting to receive their credits, the robotic object, designed as a mobile robotic service table, entered the room, carrying a tablet that invited participants to complete a 300-question questionnaire voluntarily. We compared participants’ compliance in two conditions: A Short robot composed of two modules and 95cm in height and a Tall robot consisting of three modules and 132cm in height. Our findings revealed higher compliance with the Short robot’s request, demonstrating an opposite pattern to human dynamics. We conclude that while height has a substantial social impact on human-robot interactions, it follows a unique pattern of influence. Our findings suggest that designers cannot simply adopt and implement elements from human social dynamics to robots without testing them first.

It is well established that people perceive robots as social entities, even when they are not designed for social interaction. We evaluated whether the social interpretation of robotic gestures should also be considered when turning off a robot. In the experiment, participants engaged in a brief preliminary neutral interaction while a robotic arm showed interest in their actions. At the end of the task, participants were asked to turn off the robotic arm under two conditions: (1) a Non-designed condition, where all of the robot’s engines were immediately and simultaneously turned off, as robots typically shut down; (2) a Designed condition, where the robot’s engines gradually folded inward in a motion resembling "falling asleep." Our findings revealed that all participants anthropomorphized the robot’s movement when it was turned off. In the Non-designed condition, most participants interpreted the robot’s turn-off movement negatively as if the robot had "died." In the Designed condition, most of the participants interpreted it more neutrally, stating that the robot: "went to sleep." The robot’s turn-off movement also impacted its perception, leading to higher likeability, perceived intelligence, and animacy in the Designed condition. We conclude that the impact of common edge interactions, such as turning off a robot, should be carefully designed while considering people’s automatic tendency to perceive robots as social entities.

Mindfulness meditation has vast benefits, yet is challenging for many. We designed a novel targeted warmth somaesthetic wearable and evaluated how the thermal sensation is perceived during meditation. In a qualitative study, twenty participants explored the wearable during meditation. Findings reveal participants’ rich experiences, sensations, and feelings. They perceived the technology as an appropriate tool for self-exploration. Even when participants initially felt the wearable was distracting their meditation process, they easily learned how to leverage it in their introspection process. We report on four potential roles for warmth technology: functional (pulling focal of attention), behavioral (motivating to "get back to the practice"), emotional (comforting during the lonely process), and therapeutic feelings. We conclude with design guidelines, highlighting that warmth is a promising technology for meditation if designed to encourage self-exploration of body sensations and emotions while not compromising the natural meditation practice.

Research on robotic ostracism is still scarce and has only explored its effects on adult populations. Although the results revealed important carryover effects of robotic exclusion, there is no evidence yet that those results occur in child-robot interactions. This paper provides the first exploration of robotic ostracism with children. We conducted a study using the Robotic Cyberball Paradigm in a third-person perspective with a sample of 52 children aged between five to ten years old. The experimental study had two conditions: Exclusion and Inclusion. In the Exclusion condition, children observed a peer being excluded by two robots; while in the Inclusion condition, the observed peer interacted equally with the robots. Notably, even 5-year-old children could discern when robots excluded another child. Children who observed exclusion reported lower levels of belonging and control, and exhibited higher prosocial behaviour than those witnessing inclusion. However, no differences were found in children's meaningful existence, self-esteem, and physical proximity across conditions. Our user study provides important methodological considerations for applying the Robotic Cyberball Paradigm with children. The results extend previous literature on both robotic ostracism with adults and interpersonal ostracism with children. We finish discussing the broader implications of children observing ostracism in human-robot interactions.

Opening encounters are a fundamental component of every interaction. Psychology research highlights the valence of opening encounters as one of the main factors shaping the interaction that follows. We evaluated whether opening encounters would have a similarly powerful effect on human-robot interactions. Specifically, we tested how positive and negative opening encounters with a robot would impact the subsequent interaction. Participants interacted with a robot that performed gestures communicating different valences of opening encounters: Positive, Negative, or No opening encounter. To evaluate the impact on the subsequent interaction, we measured participants' willingness to comply with a help request presented by the robot and their perception of the robot. Our results indicated that most participants in the Positive opening encounter condition helped the robot and described a positive overall perception. An opposite pattern emerged in the other two conditions. Almost none of the participants helped the robot, and the perception of the robot was less positive. Our findings suggest that opening encounters with robots should be carefully considered due to their impact on the interaction that follows.

One of the central challenges in designing autonomous vehicles concerns passenger trust and sense of safety. This challenge is related to passengers' well-established past experience with non-autonomous vehicles, which leads to concern about the absence of a driver. We explored whether it is possible to address this challenge by designing an interaction with a simple robotic object positioned on the vehicle's dashboard. The robot greeted the passenger, indicated that the vehicle was attentive to its surroundings, and informed the passenger that the drive was about to begin. We evaluated whether the robot's non-verbal behavior would provide the signals and social experience required to support passengers' trust and sense of safety. In an in-person (in-situ) experiment, participants were asked to enter an autonomous vehicle and decide if they were willing to go for a drive. As they entered the vehicle, the robot performed the designed behaviors. We evaluated the participants' considerations and experience while they made their decision. Our findings indicated that participants' trust ratings and safety-related experience were higher than those of a baseline group who did not interact with the robot. Participants also perceived the robot as providing companionship during a lonely experience. We suggest that robotic objects are a promising technology for enhancing passengers' experience in autonomous vehicles.

Human societies rely on cooperation and mutual assistance, yet individuals often prioritize personal interests over acting prosocially in daily life. To explore the potential of Human-Robot Interaction (HRI) to enhance prosocial behavior, we designed a robotic coffee machine that encourages a behavior that would benefit others. We examined the impact of embedding robotic gestures into a familiar context of making coffee in a public machine and tested participants’ willingness to fill in the water tank after making coffee. Participants’ behavior was compared to a baseline group performing the same task without the robotic gesture. Results revealed that the majority of participants in the experimental group demonstrated a willingness to fill in the water tank, indicating a prosocial inclination. Overall, participants reported a positive experience, with clear indications of their understanding of the robotic request to fill the water tank and recognition of the robot’s contribution to fostering prosocial behavior.

Affective trust and cognitive trust are fundamental elements in human-robot interactions. They impact robots’ acceptance, the level of engagement, and the tendency to rely on robots in various contexts. Opposite effects are observed when the interaction with a robot is unreliable and untrustworthy. In this study, we examined the possibility of enhancing both aspects of trust by manipulating the robot’s level of attentiveness to the participant. We focused on robotic attentiveness since it can be easily applied even to highly simple non-humanoid robots, positioning it as a method for enhancing trust for robots with different morphologies. Specifically, we evaluated whether minimal attentive robotic gestures can enhance affective and cognitive aspects of trust and whether inattentive robotic behavior can decrease them. Quantitative and qualitative results indicated that the robot’s attentiveness impacted both aspects of trust. Participants in the Attentive Robot condition reported higher affective and cognitive trust scores, smaller interpersonal distance, and a higher number of participants reported that the robot would "be there for them", in comparison to the Inattentive Robot and Baseline conditions. Our findings suggest that an attentive robotic behavior, can support human affective and cognitive trust and enhance human-robot interaction.

A wide range of studies in Human-Robot Interaction (HRI) has shown that robots can influence the social behavior of humans. This phenomenon is commonly explained by the Media Equation. Fundamental to this theory is the idea that when faced with technology (like robots), people perceive it as a social agent with thoughts and intentions similar to those of humans. This perception guides the interaction with the technology and its predicted impact. However, HRI studies have also reported examples in which the Media Equation has been violated, that is when people treat the influence of robots differently from the influence of humans. To address this gap, we propose a model of Robot Social Influence (RoSI) with two contributing factors. The first factor is a robot’s violation of a person’s expectations, whether the robot exceeds expectations or fails to meet expectations. The second factor is a person’s social belonging with the robot, whether the person belongs to the same group as the robot or a different group. These factors are primary predictors of robots’ social influence and commonly mediate the influence of other factors. We review HRI literature and show how RoSI can explain robots’ social influence in concrete HRI scenarios.

One of the main challenges parents face is recognizing and supporting the changing needs of their children. The Circle of Security (COS) psychology theory addresses this challenge by increasing parental mentalization, a parent’s ability to mentally envision her child’s mental states, and to engage in reflection on her own internal experiences. We present an exploratory design process of a tangible interface for parents of 5-7 years-old children, grounded in theoretical aspects from Attachment theory, Caregiving sensitivity theory, and COS theory. We designed three low-fidelity prototypes and evaluated them with four parents to generate initial insights about the potential of TUI as an aid for parental mentalization. Our work suggests that parents see potential in using a TUI to improve their parental mentalization abilities, however they report it is not easy and requires significant mental effort. Our work is a first step towards TUI as an aid for parental mentalization.

Family dinners introduce an opportunity for quality family time which is significant for the development of emotional skills, life satisfaction and the establishment of a strong parent-child bond. However, family dinners are constantly challenged by mobile distractions. We present the design and preliminary evaluation of a peripheral Tangible User Interface, in the form of a table spinning top. The object is aimed at enhancing family quality time by raising awareness of mobile phone distraction and motivating family members to return their focus to the family activity. A preliminary user study with three families revealed high engagement and increased motivation for stopping mobile distractions and re-engaging in the family interaction. Our results suggest the prototype can assist in regulating digital interference in a constructive and positive way.

Social awkwardness is a frequent challenge to healthy social interactions and can dramatically impact how people feel, communicate and behave. It is known that humor can invoke positive feelings and enable people to modify perspective of a situation. We explored whether using a non-humanoid robotic object performing humorous behavior can reduce social awkwardness between two strangers. The robot was peripherally incorporated into the interaction to ensure the natural social flow. We compared the impact of humorous and non-humorous robotic gestures on the human-human interaction. Objective and subjective measures indicate that despite being peripheral to the human-human interaction, the humorous robotic gestures significantly reduced the intensity of awkwardness between the strangers. Our findings suggest humorous robotic behavior can be used to enhance interpersonal relationships hindered by awkwardness and still preserve natural human-human interaction.

Social robotic behavior is commonly designed using AI algorithms which are trained on human behavioral data. This training process may result in robotic behaviors that echo human biases and stereotypes. In this work, we evaluated whether an interaction with a biased robotic object can increase participants' stereotypical thinking. In the study, a gender-biased robot moderated debates between two participants (man and woman) in three conditions: (1) The robot's behavior matched gender stereotypes (Pro-Man); (2) The robot's behavior countered gender stereotypes (Pro-Woman); (3) The robot's behavior did not reflect gender stereotypes and did not counter them (No-Preference). Quantitative and qualitative measures indicated that the interaction with the robot in the Pro-Man condition increased participants' stereotypical thinking. In the No-Preference condition, stereotypical thinking was also observed but to a lesser extent. In contrast, when the robot displayed counter-biased behavior in the Pro-Woman condition, stereotypical thinking was eliminated. Our findings suggest that HRI designers must be conscious of AI algorithmic biases, as interactions with biased robots can reinforce implicit stereotypical thinking and exacerbate existing biases in society. On the other hand, counter-biased robotic behavior can be leveraged to support present efforts to address the negative impact of stereotypical thinking.

A main challenge in incorporating autonomous vehicles into urban environments concerns communication with pedestrians crossing in front of them. We introduce a robotic object for facilitating natural crossing interactions by leveraging pedestrians’ existing crossing habits. The robot was designed to fit on the vehicle’s dashboard and simulate head gestures to indicate if it is safe to cross. We evaluated the perception of the robot as mediating the AV’s communication and the comprehension of its gestures, in an in-person experiment. Participants were asked to cross the road in front of a vehicle that was presented as having autonomous driving capabilities. The robot was placed on the vehicle’s dashboard in a location where pedestrians habitually look. The results indicated that when asked to cross, participants immediately looked toward the driver’s seat and easily noticed the robot. They consistently categorized the robot’s gestures into ”cross” or ”do-not-cross” categories and reported a strong sense of safety. Our findings suggest that robotic objects are a promising technology for mediating natural pedestrian-AV communication.

Autonomous actuated-interfaces provide a unique research opportunity for shared-control interfaces, as the human and the interface collaborate using the physical interaction modality, manipulating the same physical elements at the same time. Prior studies show that sharing control with physical modality interfaces often results in frustration and low sense-of-control. We designed and implemented adaptive behavior for shared-control actuated-interfaces that extends prior work by providing humans the ability to anticipate the autonomous action, and then accept or override it. Results from a controlled study with 24 participants indicate better collaboration in the Adaptive condition compared with the Non-adaptive one, with improved sense-of-control, feelings of teamwork, and overall collaboration quality. Our work contributes to shared-control tangible, shape-change, and actuated interfaces. We show that leveraging minimal non-verbal social cues to physically communicate the actuated-interface’s intent, coupled with providing autonomy to the human to physically accept or override the shift-in-control, improves the shared-control collaboration.

We evaluate whether an interaction with robots can influence a subsequent Human-Human Interaction without the robots' presence. Social psychology studies indicate that some social experiences have a carryover effect, leading to implicit influences on later interactions. We tested whether a social experience formed in a Human-Robot Interaction can have a carryover effect that impacts a subsequent Human-Human Interaction. We focused on ostracism, a phenomenon known to involve carryover effects that lead to prosocial behavior. Using the Robotic Ostracism Paradigm, we compared two HRI experiences: Exclusion and Inclusion, testing their impact on a Human-Human Interaction that did not involve robots. Robotic ostracism had a carryover effect that led to prosocial behavior in the Human-Human Interaction, whereby participants preferred intimate interpersonal space and displayed increased compliance. We conclude that HRI experiences may involve carryover effects that extend beyond the interaction with robots, impacting separate and different subsequent strictly human Interactions.

With recent advancements in AI, there are growing concerns about human biases implemented in AI decisions. Threats posed by AI bias may be even more drastic when applied to robots that are perceived as independent entities and are not mediated by humans. Furthermore, technology is typically perceived as objective and there is a risk that people will embrace its decisions without considering possible biases. In order to understand the extent of threats brought about by such biases, we evaluated participants’ responses to a gender-biased robot mediating a debate between two participants (male and female). The vast majority of participants did not associate the robot’s behavior with a bias, despite being informed that the robot’s algorithm is based on human examples. Participants attributed the robot’s decisions to their own performance and used explanations involving gender stereotypes. Our findings suggest that robots’ biased behaviors can serve as validation for common human stereotypes.

Having a sense of security is considered a basic human emotional need. It increases confidence, encourages exploration, and enhances relationships with others. In this study we tested the possibility of leveraging the interaction with a simple non-humanoid robot for increasing participants’ sense of security. The robotic behavior was designed with a psychology expert in attachment theory and was translated into the robot’s morphology by an animator. Specifically, the robot was designed to be attentive and responsive using lean, gaze and nodding gestures. We compared participants’ experience in the secure condition to the experience of participants who interacted with a non-responsive robot. We further compared the participants’ implicit sense of security between the robotic conditions and an additional baseline condition in which participants did not interact with the robot. Our findings indicate the potential in leveraging a simple non-humanoid robot for enhancing humans’ sense of security.

We present an actuated-interface that is not only a tangible interface but also an autonomous object, designed as an independent entity that takes a similar role to the user’s role in an anagram word game. We highlight two leading interaction paradigms: Turn-taking-actuation and Joint-actuation, and evaluate both in a qualitative interaction study with the autonomous actuated-interface. Our findings reveal that all participants perceived the interaction as a social experience. The different interaction paradigms led to different interpretations: Turn-taking-actuation was interpreted as a competitive experience, while Joint-actuation was interpreted as a collaborative experience. The interaction paradigms also influenced the intensity of emotions and perception of control, with Joint-actuation leading to more intense emotions and higher sensitivity to control in the interaction. To conclude, our findings show that it is possible to design an actuated-interface that users perceive both as a tangible interface and as a social entity with its own intent.

Robot-Robot-Human Interaction is an emerging field, holding the potential to reveal social effects involved in human interaction with more than one robot. We tested if an interaction between one participant and two non-humanoid robots can lead to negative feelings related to ostracism, and if it can impact fundamental psychological needs including control, belonging, meaningful existence, and self-esteem. We implemented a physical ball-tossing activity based on the Cyberball paradigm. The robots' ball-tossing ratio towards the participant was manipulated in three conditions: Exclusion (10%), Inclusion (33%), and Over-inclusion (75%). Objective and subjective measures indicated that the Exclusion condition led to an ostracism experience which involved feeling "rejected", "ignored", and "meaningless", with an impact on various needs including control, belonging, and meaningful existence. We conclude that interaction with more than one robot can form a powerful social context with the potential to impact psychological needs, even when the robots have no humanoid features.

Robots designed for social interaction are predicted to be employed in a wide range of environments including homes, schools, and workplaces (Bartneck & Forlizzi, 2004; Fong, Nourbakhsh, & Dautenha...

One of the challenges faced by healthy older adults is experiencing feelings of not "being-seen". Companion robots, commonly designed with zoomorphic or humanoid appearance show success among clinical older adults, but healthy older adults find them degrading. We present the design and implementation of a novel non-humanoid robot. The robot's primary function is a cognitive word game. Social interaction is conveyed as a secondary function, using non-verbal gestures, inspired by dancers' movement. In a lab study, 39 healthy older adults interacted with the prototype in 3 conditions: Companion-Function; Game-Function; and No-Function. Results show the non-verbal gestures were associated with feelings of "being-seen", and willingness to accept the robot into their home was influenced by its function, with game significantly higher than companion. We conclude that robot designers should further explore the potential of non-humanoid robots as a new class of companion robots, with a primary function that is not companionship.

Machine Learning services are integrated into various aspects of everyday life. Their underlying processes are typically black-boxed to increase ease-of-use. Consequently, children lack the opportunity to explore such processes and develop essential mental models. We present a gesture recognition research platform, designed to support learning from experience by uncovering Machine Learning building blocks: Data Labeling and Evaluation. Children used the platform to perform physical gestures, iterating between sampling and evaluation. Their understanding was tested in a pre/post experimental design, in three conditions: learning activity uncovering Data Labeling only, Evaluation only, or both. Our findings show that both building blocks are imperative to enhance children's understanding of basic Machine Learning concepts. Children were able to apply their new knowledge to everyday life context, including personally meaningful applications. We conclude that children's interaction with uncovered black boxes of Machine Learning contributes to a better understanding of the world around them.

Outdoor play is in decline, including its benefits to children's development. Coding, a typically indoor, screen-based activity, can potentially enrich outdoor play, serving as a rule-making medium. We present a coding platform that controls a programmable hardware device, enabling children to technologically-enhance their outdoor play experiences by inventing game ideas, coding them, and playing their games together with their friends. In the evaluation study, 24 children used the system to invent and play outdoor games. Results show children are able to bridge between the different domains of coding and outdoor play. They used the system to modify traditional games and invent new ones, enriching their outdoor experience. Children merged computational concepts with physical game elements, integrated physical outdoor properties as variables in their code, and were excited to see their code come to life. We conclude children can use coding to express their ideas by creating technologically-enhanced outdoor play experiences.

Machine Learning (ML) processes are integrated into devices and services that affect many aspects of daily life. As a result, basic understanding of ML concepts becomes essential for people of all ages, including children. We studied if 10--12 years old children can understand basic ML concepts through direct experience with a digital stick-like device, in a WoZ-based experiment. To assess children's understanding we applied an experimental design including a pretest, a gesture recognition training activity, and a posttest. The tests included validating children's understanding of the gesture training activity, other gesture detection processes, and application to ML processes in daily scenarios. Our findings suggest that children are able to understand basic ML concepts, and can even apply them to a new context. We conclude that ML learning activities should allow children to sample their own examples and evaluate them in an iterative way, and proper feedback should be designed to gradually scaffold understanding.

Outdoor play has known benefits for children's development, and studies show it is in decline. Heads-Up Games have been proposed as a possible solution, in some cases with an integrated coding platform to enrich play variety. In this pilot study we set out to evaluate a Scratch-based coding platform for outdoor play. The code primitives control digital features of a stick-like outdoor play object. We observed children's play patterns with the coding platform and with the play object, and report on three distinct patterns: "Basic Exploration", "Advanced Exploration", and "Game Invention". Our preliminary findings show that all children began with "Basic Exploration" and progressed either to "Advanced Exploration" or "Game Invention". With regards to outdoor play benefits, the "Game Invention" pattern was associated with more collaborative social interaction, physical activity, and "heads up" interaction. We discuss the implications for future coding platforms designed for outdoor play.

Parent-child interaction during a collaborative activity can empower children if parents are able to envision their child's mental state and regulate their behavior. However, this ability is a great challenge for many parents. We designed a simple tangible 'Awareness Object' (AO) intended to raise parents' awareness of the roles they can play and help them shift their focus to the interaction with their child. We present results from 12 parent-child interactions with the AO. Our qualitative analysis reveals that the AO raised parents' awareness of their roles during the activity and led to various types of reflection by both parents and children. In addition, the AO increased children's involvement in evaluating their parent's role, which some parents found intriguing while others found inappropriate. We conclude that a simple tangible interface can enhance parent-child interaction. However, this interaction is sensitive and should be approached with caution.

Outdoor play has been proven to be beneficial for children's development. HCI research on Heads-Up Games suggests that the well-known decline in outdoor play can be addressed by adding technology to such activities. However, outdoor play benefits such as social interaction, creative thinking, and physical activity may be compromised when digital features are added. We present the design & implementation of a novel digitally-enhanced outdoor-play prototype. Our evaluation with 48 children revealed that a non-digital version of the novel outdoor play object afforded social play and game invention. Evaluation of the digitally-enhanced version showed reduced collaborative social interaction and reduced creative thinking when compared with baseline. However, we showed that specific sensing and feedback features better supported outdoor play benefits. For example non-accumulated feedback was shown to increase collaborative play and creative thinking in comparison to accumulated feedback. We provide evidence-based recommendations for designers of outdoor play technologies.

Opening encounters are an integral element of everyday social interaction, and are essential for forming and maintaining social relationships between people. We present an abstract non-humanoid robotic object called the Greeting Machine, designed to communicate positive and negative social cues in the context of opening encounters. The design includes a small ball rolling on a larger dome, with a custom gear and lever mechanism that supports a variety of subtle movements. Gestures were designed with movement experts, and were evaluated using a physical first-person qualitative study. Our findings reveal that an abstract robot designed with no specific metaphor can effectively take part in opening encounters. Furthermore, a minimal brief movement, designed as an Approach or Avoid gesture, may be enough to evoke positive and negative experiences. The ability to create opening encounters with low Degree of Freedom abstract robots is promising, both due to the low complexity, low cost, and design flexibility of such devices, and due to the possible generalization of the Approach and Avoid gestures for a variety of morphologies.