Using Social Robots in Health Settings: Implications of Personalization on Human-Machine Communication

In view of the shortage of healthcare workers and a growing aging population, it is worthwhile to explore the applicability of new technologies in improving the quality of healthcare and reducing its cost. However, it remains a challenge to deploy such technologies in environments where individuals have limited knowledge about how to use them. Thus, this paper explores how the social robots designed for use in health settings in Australia have sought to overcome some of the limitations through personalization. Deployed in aged care and home-based care facilities, the social robots are person-centered, emphasizing the personalization of care with human-like attributes (e.g., human appearances) to engage in reciprocal communication with users. While there have been debates over the advantages and disadvantages of personalization, this paper discusses the implications of personalization on the design of the robots for enhancing engagement, empowerment and enablement in health settings

The case of classroom robots: teachers’ deliberations on the ethical tensions

Robots are increasingly being studied for use in education. It is expected that robots will have the potential to facilitate children’s learning and function autonomously within real classrooms in the near future. Previous research has raised the importance of designing acceptable robots for different practices. In parallel, scholars have raised ethical concerns surrounding children interacting with robots. Drawing on a Responsible Research and Innovation perspective, our goal is to move away from research concerned with designing features that will render robots more socially acceptable by end users toward a reflective dialogue whose goal is to consider the key ethical issues and long-term consequences of implementing classroom robots for teachers and children in primary education. This paper presents the results from several focus groups conducted with teachers in three European countries. Through a thematic analysis, we provide a theoretical account of teachers’ perspectives on classroom robots pertaining to privacy, robot role, effects on children and responsibility. Implications for the field of educational robotics are discussed.info:eu-repo/semantics/acceptedVersio

Humanization of robots: is it really such a good idea?

The aim of this review was to examine the pros and cons of humanizing social robots following a psychological perspective. As such, we had six goals. First, we defined what social robots are. Second, we clarified the meaning of humanizing social robots. Third, we presented the theoretical backgrounds for promoting humanization. Fourth, we conducted a review of empirical results of the positive effects and the negative effects of humanization on human–robot interaction (HRI). Fifth, we presented some of the political and ethical problems raised by the humanization of social robots. Lastly, we discussed the overall effects of the humanization of robots in HRI and suggested new avenues of research and development.info:eu-repo/semantics/publishedVersio

Teaching Turkish‐Dutch kindergartners Dutch vocabulary with a social robot:Does the robot's use of Turkish translations benefit children's Dutch vocabulary learning?

Providing first language (L1) translations in L2 vocabulary interventions may be beneficial for L2 vocabulary learning. However, in linguistically diverse L2 classrooms, teachers cannot provide L1 translations to all children. Social robots do offer such opportunities, as they can be programmed to speak any combination of languages. This study investigates whether providing L1 translations in a robot-assisted L2 vocabulary training facilitates children's learning. Participants were Turkish-Dutch kindergartners (n = 67) who were taught six Dutch (L2) words for which they knew the L1 (Turkish), but not the L2 Dutch form. Half of these words were taught by a Turkish-Dutch bilingual robot, alongside their Turkish translations; the other half by a monolingual Dutch robot. Children also completed Dutch and Turkish receptive vocabulary tests. Results of generalized linear regression models indicated better performance in the Dutch-only condition than in the Turkish-Dutch condition. Children with well-developed Turkish and Dutch vocabulary knowledge outperformed children with less well-developed vocabulary knowledge. The majority of children preferred working with the bilingual robot, but children's preference did not affect word learning. Thus, contrary to our prediction, we found no evidence for a facilitating effect of providing L1 translations through a robot on bilingual children's L2 word learning

User Experience Design and Evaluation of Persuasive Social Robot As Language Tutor At University : Design And Learning Experiences From Design Research

Human Robot Interaction (HRI) is a developing field where research and innovation are progressing. One domain where Human Robot Interaction has focused is in the educational sector. Various research has been conducted in education field to design social robots with appropriate design guidelines derived from user preferences, context, and technology to help students and teachers to foster their learning and teaching experience. Language learning has become popular in education due to students receiving opportunities to study and learn any interested subjects in any language in their preferred universities around the world. Thus, being the reason behind the research of using social robots in language learning and teaching in education field. To this context this thesis explored the design of language tutoring robot for students learning Finnish language at university. In language learning, motivation, the learning experience, context, and user preferences are important to be considered. This thesis focuses on the Finnish language learning students through language tutoring social robot at Tampere University. The design research methodology is used to design the persuasive language tutoring social robot teaching Finnish language to the international students at Tampere University. The design guidelines and the future language tutoring robot design with their benefits are formed using Design Research methodology. Elias Robot, a language tutoring application designed by Curious Technologies, Finnish EdTech company was used in the explorative user study. The user study involved Pepper, Social robot along with the Elias robot application using Mobile device technology. The user study was conducted in university, the students include three male participants and four female participants. The aim of the study was to gather the design requirements based on learning experiences from social robot tutor. Based on this study findings and the design research findings, the future language tutoring social robot was co-created through co design workshop. Based on the findings from Field study, user study, technology acceptance model findings, design research findings, student interviews, the persuasive social robot language tutor was designed. The findings revealed all the multi modalities are required for the efficient tutoring of persuasive social robots and the social robots persuade motivation with students to learn the language. The design implications were discussed, and the design of social robot tutor are created through design scenarios

Multi-modalities in classroom learning environments

This paper will present initial findings from the second phase of a Horizon 2020 funded project, Managing Affective-learning Through Intelligent Atoms and Smart Interactions (MaTHiSiS). The project focusses on the use of different multi-modalities used as part of the project in classrooms across Europe. The MaTHiSiS learning vision is to develop an integrated learning platform, with re-usable learning components which will respond to the needs of future education in primary, secondary, special education schools, vocational environments and learning beyond the classroom. The system comprises learning graphs which attach individual learning goals to the system. Each learning graph is developed from a set of smart learning atoms designed to support learners to achieve progression. Cutting edge technologies are being used to identify the affect state of learners and ultimately improve engagement of learners. Much research identifies how learners engage with learning platforms (c.f. [1], [2], [3]). Not only do e-learning platforms have the capability to engage learners, they provide a vehicle for authentic classroom and informal learning [4] enabling ubiquitous and seamless learning [5] within a non-linear environment. When experiencing more enjoyable interaction learners become more confident and motivated to learn and become less anxious, especially those with learning disabilities or at risk of social exclusion [6], [13]. [7] identified the importance of understanding the affect state of learners who may experience emotions such as 'confusion, frustration, irritation, anger, rage, or even despair' resulting in disengaging with learning. The MaTHiSiS system will use a range of platform agents such as NAO robots and Kinects to measure multi-modalities that support the affect state: facial expression analysis and gaze estimation [8], mobile device-based emotion recognition [9], skeleton motion using depth sensors and speech recognition. Data has been collected using multimodal learning analytics developed for the project, including annotated multimodal recordings of learners interacting with the system, facial expression data and position of the learner. In addition, interviews with teachers and learners, from mainstream education as well as learners with profound multiple learning difficulties and autism, have been carried out to measure engagement and achievement of learners. Findings from schools based in the United Kingdom, mainstream and special schools will be presented and challenges shared

Teachers’ Views on the Use of Empathic Robotic Tutors in the Classroom

In this paper, we describe the results of an interview study conducted across several European countries on teachers’ views on the use of empathic robotic tutors in the classroom. The main goals of the study were to elicit teachers’ thoughts on the integration of the robotic tutors in the daily school practice, understanding the main roles that these robots could play and gather teachers’ main concerns about this type of technology. Teachers’ concerns were much related to the fairness of access to the technology, robustness of the robot in students’ hands and disruption of other classroom activities. They saw a role for the tutor in acting as an engaging tool for all, preferably in groups, and gathering information about students’ learning progress without taking over the teachers’ responsibility for the actual assessment. The implications of these results are discussed in relation to teacher acceptance of ubiquitous technologies in general and robots in particular

Designing for Autonomy, Competence and Relatedness in Robot-Assisted Language Learning

The current number of immigrants has risen quickly in recent years due to globalization. People move to another country for economic, educational, emotional, and other reasons. As a result, immigrants need to learn the host language to integrate into their new living environment. However, the process of learning the host language for adult immigrants faces many challenges. Among those challenges, maintaining intrinsic motivation is critical for a long-term language study process and the well-being of adult immigrants. Self-Determination Theory (SDT) is a popular theoretical framework that explains human motivation, especially intrinsic motivation, through a psychological approach to understand its nature. According to SDT, humans are intrinsically motivated through the satisfaction of the three basic needs of Autonomy, Competence, and Relatedness. Many researchers have applied the theory to different topics and directions, including language learning. On the other hand, social robots have been used extensively in the language learning context due to their physical embodiments and the application of artificial intelligence in robotics. Furthermore, research has proven that social robots can create a relaxed and engaging learning environment, thus motivating language learners. The thesis designs and implements a RALL application called SAMQ using QTrobot, a humanoid social robot capable of producing body gestures, displaying different facial expressions, and multilingual communication. The study aims to investigate SAMQ’s ability to evoke intrinsic motivations of adult immigrants in learning the Finnish language. While previous research focuses on English as the second language (L2) and targets children, this thesis’s L2 is Finnish, and the learners are adult immigrants. The thesis conducts semi-structured interviews during the Pre-study phase (N=6) to gather real insights from adult immigrants living in Finland, to understand demotivating factors in their language learning experience and the unsatisfied aspects of the three basic needs. The qualitative findings from the Pre-study contribute to the design and implementation of two versions of SAMQ, aiming at evoking intrinsic motivations through satisfying unmet needs. The first version is a Quiz-only program that tests several assumptions regarding human-robot interaction (HRI). The final version of SAMQ is a more comprehensive language learning application that supports two modes of study: Learning and Quizzes. It consists of multiple modifications that address all adult immigrants’ basic needs while additionally promoting intrinsic motivation through media. The final Evaluation of SAMQ (N=6) includes a questionnaire and a semi-structured interview. The quantitative results of the questionnaire validated the ability of using social robots to evoke adult learners’ intrinsic motivation in the RALL context. The qualitative findings from the research high-light the importance of social robots’ physical embodiments in eliciting intrinsic motivation for adult learners through satisfying Relatedness. In addition, the use of voice modality creates a genuine HRI for adult learners, fulfilling both Autonomy and Competence, resulting in an engaging and smooth learning experience. Besides that, the use of adult learners’ L1 plays a crucial role in facilitating a relaxed and familiar learning environment, supplying both Competence and Relatedness. Moreover, multimedia learning materials make the learning experience more vivid and attractive. Ultimately, the result shows that accessibility and flexibility are essential attributes for adult learners to maintain their motivation for long-term language study through the satisfaction of Autonomy. Finally, the thesis proposes a design guideline for the RALL context. It consists of five design implications for evoking intrinsic motivation in adult learners through satisfying the three basic psychological needs of Autonomy, Competence, and Relatedness. The design guideline acts as a proposal for future design and implementation of RALL programs for adults and contributes to developing the human-robot interaction field