Showing papers on "Social robot published in 2020"

Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots

Abstract: Social robots have become pervasive in the tourism and hospitality service environments The empirical understanding of the drivers of visitors' intentions to use robots in such services has become an urgent necessity for their sustainable deployment Certainly, using social androids within hospitality services requires organisations' attentive commitment to value creation and fulfilling service quality expectations In this paper, via structural equation modelling (SEM) and semi-structured interviews with managers, we conceptualise and empirically test visitors' intentions to use social robots in hospitality services With data collected in Singapore's hospitality settings, we found visitors' intentions to use social robots stem from the effects of technology acceptance variables, service quality dimensions leading to perceived value, and two further dimensions from human robot interaction (HRI): empathy and information sharing Analysis of these dimensions' importance provides a deeper understanding of novel opportunities managers may take advantage of to position social robot-delivered services in tourism and hospitality strategies

A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots

Abstract: As social robots become more common, there is a need to understand how people perceive and interact with such technology. This systematic review seeks to estimate people’s attitudes toward, trust in, anxiety associated with, and acceptance of social robots; as well as factors that are associated with these beliefs. Ninety-seven studies were identified with a combined sample of over 13,000 participants and a standardized score was computed for each in order to represent the valence (positive, negative, or neutral) and magnitude (on a scale from 1 to − 1) of people’s beliefs about robots. Potential moderating factors such as the robots’ domain of application and design, the type of exposure to the robot, and the characteristics of potential users were also investigated. The findings suggest that people generally have positive attitudes towards social robots and are willing to interact with them. This finding may challenge some of the existing doubt surrounding the adoption of robotics in social domains of application but more research is needed to fully understand the factors that influence attitudes.

Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children’s learning and emotive engagement

Abstract: Pedagogical agents are typically designed to take on a single role: either as a tutor who guides and instructs the student, or as a tutee that learns from the student to reinforce what he/she knows. While both agent-role paradigms have been shown to promote student learning, we hypothesize that there will be heightened benefit with respect to students’ learning and emotional engagement if the agent engages children in a more peer-like way — adaptively switching between tutor/tutee roles. In this work, we present a novel active role-switching (ARS) policy trained using reinforcement learning, in which the agent is rewarded for adapting its tutor or tutee behavior to the child’s knowledge mastery level. To investigate how the three different child–agent interaction paradigms (tutee, tutor, and peer agents) impact children’s learning and affective engagement, we designed a randomized controlled between-subject experiment. Fifty-nine children aged 5–7 years old from a local public school participated in a collaborative word-learning activity with one of the three agent-role paradigms. Our analysis revealed that children’s vocabulary acquisition benefited from the robot tutor’s instruction and knowledge demonstration, whereas children exhibited slightly greater affect on their faces when the robot behaves as a tutee of the child. This synergistic effect between tutor and tutee roles suggests why our adaptive peer-like agent brought the most benefit to children’s vocabulary learning and affective engagement, as compared to an agent that interacts only as a tutor or tutee for the child. This work sheds light on how fixed role (tutor/tutee) and adaptive role (peer) agents support children’s cognitive and emotional needs as they play and learn. It also contributes to an important new dimension of designing educational agents — actively adapting roles based on the student’s engagement and learning needs.

Robotic transformative service research: deploying social robots for consumer well-being during COVID-19 and beyond

Abstract: Purpose: Besides the direct physical health consequences, through social isolation COVID-19 affects a considerably larger share of consumers with deleterious effects for their psychological well-being Two vulnerable consumer groups are particularly affected: older adults and children The purpose of the underlying paper is to take a transformative research perspective on how social robots can be deployed for advancing the well-being of these vulnerable consumers and to spur robotic transformative service research (RTSR) Design/methodology/approach: This paper follows a conceptual approach that integrates findings from various domains: service research, social robotics, social psychology and medicine Findings: Two key findings advanced in this paper are (1) a typology of robotic transformative service (i e entertainer, social enabler, mentor and friend) as a function of consumers' state of social isolation, well-being focus and robot capabilities and (2) a future research agenda for RTSR Practical implications: This paper guides service consumers and providers and robot developers in identifying and developing the most appropriate social robot type for advancing the well-being of vulnerable consumers in social isolation Originality/value: This study is the first to integrate social robotics and transformative service research by developing a typology of social robots as a guiding framework for assessing the status quo of transformative robotic service on the basis of which it advances a future research agenda for RTSR It further complements the underdeveloped body of service research with a focus on eudaimonic consumer well-being © 2020, Alexander P Henkel, Martina Caic, Marah Blaurock and Mehmet Okan

Mind the gap: responsible robotics and the problem of responsibility

Abstract: The task of this essay is to respond to the question concerning robots and responsibility—to answer for the way that we understand, debate, and decide who or what is able to answer for decisions and actions undertaken by increasingly interactive, autonomous, and sociable mechanisms. The analysis proceeds through three steps or movements. (1) It begins by critically examining the instrumental theory of technology, which determines the way one typically deals with and responds to the question of responsibility when it involves technology. (2) It then considers three instances where recent innovations in robotics challenge this standard operating procedure by opening gaps in the usual way of assigning responsibility. The innovations considered in this section include: autonomous technology, machine learning, and social robots. (3) The essay concludes by evaluating the three different responses—instrumentalism 2.0, machine ethics, and hybrid responsibility—that have been made in face of these difficulties in an effort to map out the opportunities and challenges of and for responsible robotics.

Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

Abstract: Over recent years, robots are increasingly being employed in several aspects of modern society. Among others, social robots have the potential to benefit education, healthcare, and tourism. To achieve this purpose, robots should be able to engage humans, recognize users’ emotions, and to some extent properly react and "behave" in a natural interaction. Most robotics applications primarily use visual information for emotion recognition, which is often based on facial expressions. However, the display of emotional states through facial expression is inherently a voluntary controlled process that is typical of human–human interaction. In fact, humans have not yet learned to use this channel when communicating with a robotic technology. Hence, there is an urgent need to exploit emotion information channels not directly controlled by humans, such as those that can be ascribed to physiological modulations. Thermal infrared imaging-based affective computing has the potential to be the solution to such an issue. It is a validated technology that allows the non-obtrusive monitoring of physiological parameters and from which it might be possible to infer affective states. This review is aimed to outline the advantages and the current research challenges of thermal imaging-based affective computing for human–robot interaction.

Trust in Robots: Challenges and Opportunities

Abstract: To assess the state-of-the-art in research on trust in robots and to examine if recent methodological advances can aid in the development of trustworthy robots. While traditional work in trustworthy robotics has focused on studying the antecedents and consequences of trust in robots, recent work has gravitated towards the development of strategies for robots to actively gain, calibrate, and maintain the human user’s trust. Among these works, there is emphasis on endowing robotic agents with reasoning capabilities (e.g., via probabilistic modeling). The state-of-the-art in trust research provides roboticists with a large trove of tools to develop trustworthy robots. However, challenges remain when it comes to trust in real-world human-robot interaction (HRI) settings: there exist outstanding issues in trust measurement, guarantees on robot behavior (e.g., with respect to user privacy), and handling rich multidimensional data. We examine how recent advances in psychometrics, trustworthy systems, robot-ethics, and deep learning can provide resolution to each of these issues. In conclusion, we are of the opinion that these methodological advances could pave the way for the creation of truly autonomous, trustworthy social robots.

Vulnerable robots positively shape human conversational dynamics in a human-robot team.

Abstract: Social robots are becoming increasingly influential in shaping the behavior of humans with whom they interact. Here, we examine how the actions of a social robot can influence human-to-human communication, and not just robot–human communication, using groups of three humans and one robot playing 30 rounds of a collaborative game (n = 51 groups). We find that people in groups with a robot making vulnerable statements converse substantially more with each other, distribute their conversation somewhat more equally, and perceive their groups more positively compared to control groups with a robot that either makes neutral statements or no statements at the end of each round. Shifts in robot speech have the power not only to affect how people interact with robots, but also how people interact with each other, offering the prospect for modifying social interactions via the introduction of artificial agents into hybrid systems of humans and machines.

Child–robot relationship formation: A narrative review of empirical research

Abstract: This narrative review aimed to elucidate which robot-related characteristics predict relationship formation between typically-developing children and social robots in terms of closeness and trust. Moreover, we wanted to know to what extent relationship formation can be explained by children’s experiential and cognitive states during interaction with a robot. We reviewed 86 journal articles and conference proceedings published between 2000 and 2017. In terms of predictors, robots’ responsiveness and role, as well as strategic and emotional interaction between robot and child, increased closeness between the child and the robot. Findings about whether robot features predict children’s trust in robots were inconsistent. In terms of children’s experiential and cognitive states during interaction with a robot, robot characteristics and interaction styles were associated with two experiential states: engagement and enjoyment/liking. The literature hardly addressed the impact of experiential and cognitive states on closeness and trust. Comparisons of children’s interactions with robots, adults, and objects showed that robots are perceived as neither animate nor inanimate, and that they are entities with whom children will likely form social relationships. Younger children experienced more enjoyment, were less sensitive to a robot’s interaction style, and were more prone to anthropomorphic tendencies and effects than older children. Tailoring a robot’s sex to that of a child mainly appealed to boys.

Exploring Human-Robot Interaction with the Elderly: Results from a Ten-Week Case Study in a Care Home

Abstract: Ageing societies and the associated pressure on the care systems are major drivers for new developments in socially assistive robotics. To understand better the real-world potential of robot-based assistance, we undertook a 10-week case study in a care home involving groups of residents, caregivers and managers as stakeholders. We identified both, enablers and barriers to the potential implementation of robot systems. The study employed the robot platform Pepper, which was deployed with a view to understanding better multi-domain interventions with a robot supporting physical activation, cognitive training and social facilitation. We employed the robot in a group setting in a care facility over the course of 10 weeks and 20 sessions, observing how stakeholders, including residents and caregivers, appropriated, adapted to, and perceived the robot. We also conducted interviews with 11 residents and caregivers. Our results indicate that the residents were positively engaged in the training sessions that were moderated by the robot. The study revealed that such humanoid robots can work in a care home but that there is a moderating person needed, that is in control of the robot.

The Humanoid Robot NAO as Trainer in a Memory Program for Elderly People with Mild Cognitive Impairment

Abstract: Many studies on social interaction have used the humanoid robot NAO. In the present paper, we described our project designed to address the growing unmet need for alternative approaches to slowing the progression of cognitive decline in Mild Cognitive Impairment patients. NAO is the experimental platform used in an ecological setting: a center for the treatment of cognitive disorders and dementia of the Italian health service. This paper describes the study addressed to evaluate the effectiveness of human–robot interaction to reinforce therapeutic behavior and treatments adherence and presents the latest findings of functional tests and users investigation recently conducted. The robot was programmed to implement some tasks from the usual memory-training program protocol. In different training conditions, subjects participated in sessions with the support of NAO or only from the psychologist while the interaction was recorded for subsequent exploration. Data indicated that memory training with NAO resulted in an increase of visual gaze from patients and reinforce of therapeutic behavior reducing, in some cases, depressive symptoms. Unexpectedly, significant changes in prose memory and verbal fluency measures were detected. These findings suggest that further research on robotics in ecological settings is necessary to determine the extent to which they can effectively support clinical practice.

Dietary Composition Perception Algorithm Using Social Robot Audition for Mandarin Chinese

Abstract: As the problem of an aging population becomes more and more serious, social robots have an increasingly significant influence on human life. By employing regular question-and-answer conversations or wearable devices, some social robotics products can establish personal health archives. But those robots are unable to collect diet information automatically through robot vision or audition. A healthy diet can reduce a person’s risk of developing cancer, diabetes, heart disease, and other age-related diseases. In order to automatically perceive the dietary composition of the elderly by listening to people’s chatting, this paper proposed a chat-based automatic dietary composition perception algorithm (DCPA). DCPA uses social robot audition to understand the semantic information and percept dietary composition for Mandarin Chinese. Firstly, based on the Mel-frequency cepstrum coefficient and convolutional neural network, a speaker recognition method is designed to identify speech data. Based on speech segmentation and speaker recognition algorithm, an audio segment classification method is proposed to distinguish different speakers, store their identity information and the sequence of expression in a speech conversation. Secondly, a dietetic lexicon is established, and two kinds of dietary composition semantic understanding algorithms are proposed to understand the eating semantics and sensor dietary composition information. To evaluate the performance of the proposed DCPA algorithm, we implemented the proposed DCPA in our social robot platform. Then we established two categories of test datasets relating to a one-person and a multi-person chat. The test results show that DCPA is capable of understanding users’ dietary compositions, with an F1 score of 0.9505, 0.8940 and 0.8768 for one-person talking, a two-person chat and a three-person chat, respectively. DCPA has good robustness for obtaining dietary information.

The Persistence of First Impressions: The Effect of Repeated Interactions on the Perception of a Social Robot

Abstract: Numerous studies in social psychology have shown that familiarization across repeated interactions improves people’s perception of the other. If and how these findings relate to human-robot interaction (HRI) is not well understood, even though such knowledge is crucial when pursuing long-term interactions. In our work, we investigate the persistence of first impressions by asking 49 participants to play a geography game with a robot. We measure how their perception of the robot changes over three sessions with three to ten days of zero exposure in between. Our results show that different perceptual dimensions stabilize within different time frames, with the robot’s competence being the fastest to stabilize and perceived threat the most fluctuating over time. We also found evidence that perceptual differences between robots with varying levels of humanlikeness persist across repeated interactions. This study has important implications for HRI design as it sheds new light on the influence of robots’ embodiment and interaction abilities. Moreover, it also impacts HRI theory as it presents novel findings contributing to research on the uncanny valley and robot perception in general. CCS CONCEPTS •Human-centered computing → Empirical studies in HCI; Natural language interfaces; •Computer systems organization →Robotics; •Computing methodologies →Intelligent agents. ACM Reference Format: Maike Paetzel, Giulia Perugia, and Ginevra Castellano. 2020. The Persistence of First Impressions: The Effect of Repeated Interactions on the Perception of a Social Robot. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’20), March 23–26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/ 3319502.3374786

Persuasive Robots Acceptance Model (PRAM): Roles of Social Responses Within the Acceptance Model of Persuasive Robots

Abstract: In the last years, there have been rapid developments in social robotics, which bring about the prospect of their application as persuasive robots to support behavior change. In order to guide related developments and pave the way for their adoption, it is important to understand the factors that influence the acceptance of social robots as persuasive agents. This study extends the technology acceptance model by including measures of social responses. The social responses include trusting belief, compliance, liking, and psychological reactance. Using the Wizard of Oz method, a laboratory experiment was conducted to evaluate user acceptance and social responses towards a social robot called SociBot. This robot was used as a persuasive agent in making decisions in donating to charities. Using partial least squares method, results showed that trusting beliefs and liking towards the robot significantly add the predictive power of the acceptance model of persuasive robots. However, due to the limitations of the study design, psychological reactance and compliance were not found to contribute to the prediction of persuasive robots’ acceptance. Implications for the development of persuasive robots are discussed.

Mutual shaping in the design of socially assistive robots: A case study on social robots for therapy

Abstract: This paper offers a case study in undertaking a mutual shaping approach to the design of socially assistive robots. We consider the use of social robots in therapy, and we present our results regarding this application, but the approach is generalisable. Our methodology combines elements of user-centered and participatory design with a focus on mutual learning. We present it in full alongside a more general guide for application to other areas. This approach led to valuable results concerning mutual shaping effects and societal factors regarding the use of such robots early in the design process. We also measured a significant shift in participant robot acceptance pre-/post-study, demonstrating that our approach led to the two-way sharing and shaping of knowledge, ideas and acceptance.

The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions to Use Social Robots

Abstract: Conceptual research on robots and privacy has increased but we lack empirical evidence about the prevalence, antecedents, and outcomes of different privacy concerns about social robots. To fill this gap, we present a survey, testing a variety of antecedents from trust, technology adoption, and robotics scholarship. Respondents are most concerned about data protection on the manufacturer side, followed by social privacy concerns and physical concerns. Using structural equation modeling, we find a privacy paradox, where the perceived benefits of social robots override privacy concerns.

Research Trends in Social Robots for Learning

Abstract: With the growth in the number of market-available social robots, there is an increasing interest in research on the usage of social robots in education This paper proposes a summary of trends highlighting current research directions and potential research gaps for social robots in education We are interested in design aspects and instructional setups used to evaluate social robotics system in an educational setting The literature demonstrates that as the field grows, setup, methodology, and demographics targeted by social robotics applications seem to settle and standardize—a tutoring Nao robot with a tablet in front of a child seems the stereotypical social educational robotics setup An updated review on social robots in education is presented here We propose, first, an analysis of the pioneering works in the field Secondly, we explore the potential for education to be the ideal context to investigate central human-robot interaction research questions A trend analysis is then proposed demonstrating the potential for educational context to nest impactful research from human-robot interaction

Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders

Abstract: This study is a randomized control trial aimed at testing the role of a human-assisted social robot as an intervention mediator in a socio-emotional understanding protocol for children with autism spectrum disorders (ASD). Fourteen children (4–8 years old) were randomly assigned to 10 sessions of a cognitive behavioural therapy (CBT) intervention implemented in a group setting either with or without the assistance of a social robot. The CBT protocol was based on Rational Emotive Behaviour Therapy (REBT) principles. Pre- and post-intervention assessments were conducted using the Test of Emotional Comprehension (TEC) and the Emotional Lexicon Test (ELT). Substantial improvements in contextualized emotion recognition, comprehension and emotional perspective-taking through the use of human-assisted social robots were attained.

Social Robots in Therapy and Care

Abstract: This work presents a comprehensive overview of social robots in therapy and the healthcare of children, adults, and elderly populations. According to recent evidence in this field, the primary outcomes and limitations are highlighted. This review points out the implications and requirements for the proper deployment of social robots in therapy and healthcare scenarios. Social robots are a current trend that is being studied in different healthcare services. Evidence highlights the potential and favorable results due to the support and assistance provided by social robots. However, some side effects and limitations are still under research. Social robots can play various roles in the area of health and well-being. However, further studies regarding the acceptability and perception are still required. There are challenges to be addressed, such as improvements in the functionality and robustness of these robotic systems.

Visual Programming Environments for End-User Development of intelligent and social robots, a systematic review

Abstract: Robots are becoming interactive and robust enough to be adopted outside laboratories and in industrial scenarios as well as interacting with humans in social activities. However, the design of engaging robot-based applications requires the availability of usable, flexible and accessible development frameworks, which can be adopted and mastered by researchers and practitioners in social sciences and adult end users as a whole. This paper surveys Visual Programming Environments aimed at enabling a paradigm fostering the so-called End-User Development of applications involving robots with social capabilities. The focus of this article is on those Visual Programming Environments that are designed to support social research goals as well as to cater for professional needs of people not trained in more traditional text-based computer programming languages. This survey excludes interfaces aimed at supporting expert programmers, at allowing industrial robots to perform typical industrial tasks (such as pick and place operations), and at teaching children how to code. After having performed a systematic search, sixteen programming environments have been included in this survey. Our goal is two-fold: first, to present these software tools with their technical features and Authoring Artificial Intelligence modeling approaches, and second, to present open challenges in the development of Visual Programming Environments for end users and social researchers, which can be informative and valuable to the community. The results show that the most recent such tools are adopting distributed and Component-Based Software Engineering approaches and web technologies. However, few of them have been designed to enable the independence of end users from high-tech scribes. Moreover, findings indicate the need for (i) more objective and comparative evaluations, as well as usability and user experience studies with real end users; and (ii) validations of these tools for designing applications aimed at working “in-the-wild” rather than only in laboratories and structured settings.

Dynamic Emotion Understanding in Human–Robot Interaction Based on Two-Layer Fuzzy SVR-TS Model

Abstract: Two-layer fuzzy support vector regression-Takagi–Sugeno (TLFSVR-TS) model is proposed for emotion understanding in human–robot interaction (HRI), where the real-time dynamic emotion is recognized according to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make HRI run smoothly. TLFSVR-TS considers about the priori knowledge inferred from human personal preference to reduce the uncertainty of various people, and multiple support vector regression (SVR) corresponding to different genders/provinces/ages of human to guarantee the local learning ability. Preliminary application experiments are performed in the developing emotional social robot system, where 30 volunteers experience the scenario of “drinking in the bar.” Results show that the proposal receives higher understanding accuracy than that of TLFSVR, kernel fuzzy ${c}$ -means clustering is fused with SVR, and SVR.

Mini: A New Social Robot for the Elderly

Abstract: The unceasing aging of the population is leading to new problems in developed countries. Robots represent an opportunity to extend the period of independent living of the elderly as well as to ameliorate their economic burden and social problems. We present a new social robot, Mini, specifically designed to assist and accompany the elderly in their daily life either at home or in a nursing facility. Based on the results of several meetings with experts in this field, we have built a robot able to provide services in the areas of safety, entertainment, personal assistance and stimulation. Mini supports elders and caregivers in cognitive and mental tasks. We present the robot platform and describe the software architecture, particularly focussing on the human–robot interaction. We give in detail how the robot operates and the interrelation of the different modules of the robot in a real use case. In the last part of the paper, we evaluated how users perceive the robot. Participants reported interesting results in terms of usability, appearance, and satisfaction. This paper describes all aspects of the design and development of a new social robot that can be used by other researchers who face the multiple challenges of creating a new robotic platform for older people.

When AI meets PC: exploring the implications of workplace social robots and a human-robot psychological contract

Abstract: The psychological contract refers to the implicit and subjective beliefs regarding a reciprocal exchange agreement, predominantly examined between employees and employers. While contemporary contra...

An extended framework for characterizing social robots.

Abstract: Social robots are becoming increasingly diverse in their design, behavior, and usage. In this chapter, we provide a broad-ranging overview of the main characteristics that arise when one considers social robots and their interactions with humans. We specifically contribute a framework for characterizing social robots along seven dimensions that we found to be most relevant to their design. These dimensions are: appearance, social capabilities, purpose and application area, relational role, autonomy and intelligence, proximity, and temporal profile. Within each dimension, we account for the variety of social robots through a combination of classifications and/or explanations. Our framework builds on and goes beyond existing frameworks, such as classifications and taxonomies found in the literature. More specifically, it contributes to the unification, clarification, and extension of key concepts, drawing from a rich body of relevant literature. This chapter is meant to serve as a resource for researchers, designers, and developers within and outside the field of social robotics. It is intended to provide them with tools to better understand and position existing social robots, as well as to inform their future design.

A Social Robot for Rehabilitation: Expert Clinicians and Post-Stroke Patients’ Evaluation Following a Long-Term Intervention

Abstract: We developed a novel gamified system for post-stroke long-term rehabilitation, using the humanoid robot Pepper (Soft Bank, Aldebaran). Here, we present a participatory-design study with insights from both expert clinicians and from stroke patients who underwent a long-term intervention with the robot. We first present the results of a qualitative study with expert clinicians $(\mathrm{n}=12)$ on the compatibility of this system with the needs of post-stroke patients, and then the preliminary results of a long-term intervention study with post-stroke participants $(\mathrm{n}=4)$ in a rehabilitation facility. Both the clinicians and the patients found the robot and the gamified system engaging, motivating and meeting the needs of upper limb rehabilitation. The clinicians gave specific recommendations that may be applicable to a wide range of technologies for post-stroke rehabilitation. ACM Reference format: Ronit Feingold Polak and Shelly Levy-Tzedek. 2020. A Social Robot for Rehabilitation: Expert Clinicians and Post-Stroke Patients’ Evaluation Following a Long-Term Intervention. In Proceedings of HRI ’20: 2020 ACM/IEEE International Conference on Human-Robot Interaction, March 24–26, 2020, Cambridge, UK. ACM, NewYork, NY, USA, 10 pages. https://doi.org/10.1145/3319502.3374797

A Robotic Positive Psychology Coach to Improve College Students’ Wellbeing

Abstract: A significant number of college students suffer from mental health issues that impact their physical, social, and occupational outcomes. Various scalable technologies have been proposed in order to mitigate the negative impact of mental health disorders. However, the evaluation for these technologies, if done at all, often reports mixed results on improving users' mental health. We need to better understand the factors that align a user's attributes and needs with technology-based interventions for positive outcomes. In psychotherapy theory, therapeutic alliance and rapport between a therapist and a client is regarded as the basis for therapeutic success. In prior works, social robots have shown the potential to build rapport and a working alliance with users in various settings. In this work, we explore the use of a social robot coach to deliver positive psychology interventions to college students living in on-campus dormitories. We recruited 35 college students to participate in our study and deployed a social robot coach in their room. The robot delivered daily positive psychology sessions among other useful skills like delivering the weather forecast, scheduling reminders, etc. We found a statistically significant improvement in participants' psychological wellbeing, mood, and readiness to change behavior for improved wellbeing after they completed the study. Furthermore, students' personality traits were found to have a significant association with intervention efficacy. Analysis of the post-study interview revealed students' appreciation of the robot's companionship and their concerns for privacy.