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Relationships between user experiences and children's perceptions of the education robot
Abstract
The purpose of this study is to investigate the biological, mental, social, moral, and educational perceptions of young children of the intelligent robot iRobiQ and to explore the effects of user experience on them. The interview was conducted with 111 five-year-old children attending two kindergartens and two childcare centers in which iRobiQ had been purchased and had been in use since March 2009. The young children interacted with the robot for one hour or less everyday over a period of two weeks or less. The robot contents were related to the socio-emotional perceptions of robots and had a high level of human-robot interactions, such as ¿Talking with the Robot¿ or ¿Attendance Check.¿ Children who experienced the ¿voice¿ and ¿touch screen¿ functions of the robot showed higher educational perception. The social and educational perception was higher when the robot was placed in a classroom than when it was placed in the hallway or in the office. The results indicated that robot content focusing on socio-emotional characteristics should be developed for educational purposes and that a robot should be placed in the classroom for individual use.
... Insights-driven interviews are used to elicit perspectives, attitudes and opinions in order to evaluate the use, or potential use of, robots with various groups in various different settings. These include older people's domestic settings [25,71,73], older-care facilities [29,44,72,74,76], and living labs [85,88], for children in educational settings [36,87,89], and for workers in industrial and clinical settings [31,35,61,77,90] and at an airport [40]. They are used to investigate the social context into which the robot is expected to fit [25,73], and the potential use of robots for older users [30,33,84] and children [89]. ...
... These include older people's domestic settings [25,71,73], older-care facilities [29,44,72,74,76], and living labs [85,88], for children in educational settings [36,87,89], and for workers in industrial and clinical settings [31,35,61,77,90] and at an airport [40]. They are used to investigate the social context into which the robot is expected to fit [25,73], and the potential use of robots for older users [30,33,84] and children [89]. ...
... Most of these studies use systematic qualitative analysis techniques, including audio-recording, transcription and thematic analysis [26,29,31,33,35,40,42,44,[58][59][60][61][73][74][75]85,86,[88][89][90]. Less commonly, researchers used a more design-driven approach to data analysis, such as affinity diagrams [32], or a combination of the above techniques [40,75]. ...
The field of human–robot interaction (HRI) is young and highly inter-disciplinary, and the approaches, standards and methods proper to it are still in the process of negotiation. This paper reviews the use of qualitative methods and approaches in the HRI literature in order to contribute to the development of a foundation of approaches and methodologies for these new research areas. In total, 73 papers that use qualitative methods were systematically reviewed. The review reveals that there is widespread use of qualitative methods in HRI, but very different approaches to reporting on it, and high variance in the rigour with which the approaches are applied. We also identify the key qualitative methods used. A major contribution of this paper is a taxonomy categorizing qualitative research in HRI in two dimensions: by ’study type’ and based on the specific qualitative method used.
... In [27] results of using intelligent robot iRobiQ in early childhood education are presented. The robot was used as teaching assistant for 111 five-year-old children attending two kindergartens and two childcare centers. ...
... Case Study Key Points iRobiQ as teaching assistant, 111 fiveyear-old children in two kindergartens and two childcare centers, two-week study [27] Robots seem to be more effective when in classrooms, close to children and used by individuals. ...
... Several of the approaches explicitly mention testing in classroom environments. Such approaches were for instance the ones presented in [27], [52], [28], [60], [26], [34], [61], [55], [54], [31], [33] and [49]. Certain of these approaches such as the ones presented in [27], [28], [26] and [61] explicitly mention testing in different classes and/or different facilities. ...
Educational technology constitutes an important aspect in modern education providing unique learning experiences to students and improving their learning. Technological resources (especially computers) have been integrated in education for decades. However, integration of educational technology in early childhood education is a more recent trend compared to the other levels of education. This fact creates the need to develop, apply and study application of resources and methodologies specifically addressed to young children. Artificial Intelligence approaches have been incorporated to educational technology resources providing improved interaction to learners. In this paper, Artificial Intelligence methods exploited in the context of early childhood educational technology are surveyed. The discussion mainly concerns computer-based learning systems incorporating intelligent methods (e.g., Intelligent Tutoring and Adaptive Educational Hypermedia Systems) and educational robots addressed to early childhood. To the best of the author’s knowledge, such issues have not been thoroughly discussed till now in literature.
... These assistants provide support in hard processes or tasks that could be dangerous to human beings [2]. On the other hand, there is another kind of automated assistants that are dedicated to providing their functionalities for helping in different daily activities at the office or at home [3]. ...
... According to a related study [3] about the biological, mental, social, moral, and educational perceptions of young children of the intelligent robot iRobiQ, the results have shown that robots may possess contents and functions to promote the social and emotional interactions between the robots and children. It was conducted an interview with more than one hundred five-year-old children attending two kindergartens and two childcare centers in which iRobiQ had been purchased. ...
... The future will bring humans into contact with robots in a variety of unstructured interactions, many of which will involve engaging robots in verbal dialogue. This includes in-store sales [1], education [2], service interactions [3], and rehabilitation [4]. In any interaction like this, linguistic nuances and positive or negative valence of social behavior will impact the result of the interaction. ...
... We used the Pepper Robot by Softbank Robotics [37] (a research robot provided for participation in the RoboCup Social Standard Platform League). 2 Pepper is a humanoid robot with arms, a head with cameras and microphones, mobility, and voice abilities. See it pictured in Fig. 1. ...
As robots are increasingly endowed with social and communicative capabilities, they will interact with humans in more settings, both collaborative and competitive. We explore human-robot relationships in the context of a competitive Stackelberg Security Game. We vary humanoid robot expressive language (in the form of "encouraging" or "discouraging" verbal commentary) and measure the impact on participants' rationality, strategy prioritization, mood, and perceptions of the robot. We learn that a robot opponent that makes discouraging comments causes a human to play a game less rationally and to perceive the robot more negatively. We also contribute a simple open source Natural Language Processing framework for generating expressive sentences, which was used to generate the speech of our autonomous social robot.
... According to Chang et al. (2010) reported that even though they knew that the used robot was not a real person or human, students accepted robots as authority because of the robots' humanoid appearance and behaviours. Hyun, Yoon, & Son (2010) pointed that, the robot's facial expressions and speech imitation skills was very useful to teachers and thanks to ability of robots again and again speech feature. ...
... In studies conducted with iRobiQ, Yoon (2009), Hsiao et al. (2012), and Wei et al. (2011) used similar facial expressions. Additionally, Hyun et al. (2010) examined robots in the students' education in terms of mental, social, moral and educational perceptions. As a result of the study, they pointed out that robot contents should certainly contain humanoid emotions (sadness, jubilation, astonished etc.) and also should be used in individualized instruction in classes. ...
In Turkey and the world, some studies are carried out to support student’s cognitive and social development with activities such as robot competitions and robot camps. Additionally, technological materials for robot-aided learning environment have started to become widespread. Robot-aided applications can provide multimedia as well as interactions such as motion, appearance, and touch to the learners. Because of these abilities, robots have an important potential especially for education of mentally retarded students. The studies, in which activities including feedbacks given by humanoid robots are designed and applied, will make contributions to this area for revealing the potential and improving the effective applications like integration of technology into the field of education and the creation of innovative learning environments. The purpose of this study was to examine interactions of students with mild mental retardation in terms of feedback types in the robot-assisted learning environment, analyse participations of students with mild mental retardation in this environment activities and compare the investigation of interactions in terms of feedback types. In this way, it was aimed to create design proposals for feedback types in robot-assisted learning environment to be designed for students with mental disability. Humanoid robot assisted activities prepared according to ASSURE instructional design method. This study was conducted in six sessions on six students with mild mental retardation who were registered in the Guidance and Research Centre (GRC). Being one of the qualitative research methods, case study was used in this study. In the study, data were gathered by carrying out interviews and observations. In order to reach the notions and correlations explaining the data, the methods of content analysis and descriptive analysis were used. In this study, it was observed that the students met the humanoid robot’s feedbacks pleasantly and excitedly, they commented and responded amusedly. The use of feedbacks in this study drew the students’ attentions and increased their motivation. However, there were differences in terms of reaction types in their reactions to the robot’s feedback. While feedbacks considered as the most remarkable and interacting by the students were arm, bodily and voice feedbacks, the least responded feedbacks were head movement feedbacks and feedbacks formed through the robot’s screen. As a result of interviews made with the teachers, it was specified that humanoid robot make positive contributions to the student motivation and teaching of the lesson. The teachers stated that according to general evaluation forms and the results of their measurements, robot-aided education was useful and helpful at the classroom management, provided quick and permanent learning, and increased motivation and participation of activities.
... Research regarding educational robots and machines in learning institutions has been conducted for many years, targeting not only young scholars but also kindergarten children. The authors in [13] investigate the relationships between user experience and children's perceptions about educational robots. The study suggested that robot content concentrating on socio-emotional traits should be created for educational purposes and that a robot should be located in the classroom for individual use. ...
... Thanks to the advances in robotic technology, human robot interaction (HRI) is popularly used for a variety of applications, including in-store sales [1], entertainment [2], education [3], personal healthcare [4], and therapy [5]. As an increasing amount of the human workforce is replaced by robots, HRI should naturally be widely used in education [2,4]. ...
The use of humanoid robots within a therapeutic role, that is, helping individuals with social disorders, is an emerging field, but it remains unexplored in terms of concentration training. To seamlessly integrate humanoid robots into concentration games, an investigation into the impacts of human robot interactive proxemics on concentration-training games is particularly important. In the case of an epidemic diffusion especially—for example, during the COVID-19 pandemic—HRI games may help in the therapeutic phase, significantly reducing the risk of contagion. In this paper, concentration games were designed by action imitation involving 120 participants to verify the hypothesis. Action-imitation accuracy, the assessment of emotional expression, and a questionnaire were compared with analysis of variance (ANOVA). Experimental results showed that a 2 m distance and left-front orientation for a human and a robot are optimal for human robot interactive concentration training. In addition, females worked better than males did in HRI imitation games. This work supports some valuable suggestions for the development of HRI concentration-training technology, involving the designs of friendlier and more useful robots, and HRI game scenarios.
... IRobiQ is used for cognitive training, medication reminder, telepresence communication, entertainment, and vital signs monitoring in healthcare [21]. It is also well accepted by children in early childhood educational settings [22]. ...
Objective
We introduced a humanoid robot for the use of techno-psychological distraction techniques in children aged 4–10 to reduce their anxiety and improve their behaviour during dental treatment.
Materials and methods
Two hundred children (98 boys, 102 girls; mean age: 6.5 ± 1.66 years) appointed for first time for dental caries were included and randomly divided into two groups [N = 100 for each group; RG: Robot Group (accompanied by the robot), CG: Control Group (without robot accompaniment)]. Half of the children were treated under local anaesthesia (infiltration anaesthesia) (n = 50 within each group) and half of the children were treated without any local anaesthesia (n = 50 within each group) within each group. The success rate of the new robotic distraction technique was evaluated by using Parental Corah Dental Anxiety Scale, Facial Image Scale (FIS), physiological pulse rate and Frankl Behaviour Rating Scale (FBRS).
Result
Pulse rates, which measured during treatment and after treatment, were statistically higher in CG than in RG (p < .05). After dental treatment, the FIS score was significantly higher in CG than RG (p < .05). 88.3% of the children in RG stated that they wanted the robot to be with them at the next treatment session.
Conclusions
Robotic technology can successfully help in coping with dental anxiety and stress, and helps children to behave better in dental office.
... iRobiQ and Zenbo are two commercially available vehicle robots that have a toy-like appearance. The first one has a display and face lamps that are used to express emotions [66]. Zenbo is a more sophisticated robot with a ball-shaped torso, neck, and head with a touch-display face. ...
Emotions are important in many aspects of human behavior. Emotions are displayed on human faces, they are reflected in human memory, and they even influence human intelligence. The creation of robots that try to mimic humans arises the question of how the concept of emotion can be transferred to robots. There is no unique answer to the question, however many robots that leverage emotions exist. By summarizing the work done on these robots we try to enlighten the relations between robots and emotions from several perspectives. We first identify how artificial emotion can be defined in a robotic system. Next, we investigate the possible roles of emotions in robotic behavior models and analyze different implementations of the concept of emotion in these models. Finally, we elaborate on the evaluation of how emotions influence human-robot interaction. For this purpose, we qualitatively analyzed a selected set of robots that include emotions in their model. Considering the diversity of state-of-the-art approaches to using emotions in robots, we try to present the findings in a structured and comprehensive way that could be valuable for future researchers.
... For example, Beran et al. asked questions about a robot to 198 children and found that a significant proportion of children were able to ascribe behavioural and cognitive characteristics to the robot [6]. Similarly, Hyun et al. interviewed 111 five-yearold children to explore their social, educational and moral perceptions of an iRobiQ robot. 2 The results indicate that the children's social and educational perception of the robot was higher when it was placed in the classroom compared to hallways or office [34]. ...
As robots are entering into educational fields to enhance children's learning, it becomes relevant to explore different methods of learning in the area of child-robot interaction. In this article, we present an autonomous educational system incorporating a social robot to enhance children's handwriting skills. The system provides a one-to-one learning scenario based on the learning-by-teaching approach where a tutor-child assess the handwriting skills of a learner-robot. The robot's writing was generated by an algorithm incorporating human-inspired movements and could reproduce a set of writing errors. We tested the system by conducting two multi-session studies. In the first study, we assigned the robot two contrasting competencies: 'learning' and 'non-learning'. We measured the differences in children's learning gains and changes in their perceptions of the learner-robot. The second study followed a similar interaction scenario and research questions, but this time the robot performed three learning competencies: 'continuous-learning'; 'non-learning' and 'personalised-learning'. The findings of these studies show that the children learnt with the robot that exhibits learning competency and children's learning and perceptions of the robot changed as interactions unfold, confirming the need for longitudinal studies. This research supports that the contrasting learning competencies of social robots can impact children's learning differently in peer-learning scenarios.
... For example, Beran et al. asked questions about a robot to 198 children and found that a significant proportion of children were able to ascribe behavioural and cognitive characteristics to the robot [6]. Similarly, Hyun et al. interviewed 111 five-yearold children to explore their social, educational and moral perceptions of an iRobiQ robot. 2 The results indicate that the children's social and educational perception of the robot was higher when it was placed in the classroom compared to hallways or office [34]. ...
As robots are entering into educational fields to enhance children’s learning, it becomes relevant to explore different methods of learning in the area of child–robot interaction. In this article, we present an autonomous educational system incorporating a social robot to enhance children’s handwriting skills. The system provides a one-to-one learning scenario based on the learning-by-teaching approach where a tutor-child assess the handwriting skills of a learner-robot. The robot’s writing was generated by an algorithm incorporating human-inspired movements and could reproduce a set of writing errors. We tested the system by conducting two multi-session studies. In the first study, we assigned the robot two contrasting competencies: ‘learning’ and ‘non-learning’. We measured the differences in children’s learning gains and changes in their perceptions of the learner-robot. The second study followed a similar interaction scenario and research questions, but this time the robot performed three learning competencies: ‘continuous-learning’; ‘non-learning’ and ‘personalised-learning’. The findings of these studies show that the children learnt with the robot that exhibits learning competency and children’s learning and perceptions of the robot changed as interactions unfold, confirming the need for longitudinal studies. This research supports that the contrasting learning competencies of social robots can impact children’s learning differently in peer-learning scenarios.
... User perceptions are central to determining future user experience and usability of various systems (Hyun et al. 2010). The initial system evaluation was aimed at providing feedback on user perception, usability of the system and its adequacy for instructional purposes. ...
Human–Computer interaction, including technology-aided instruction, is beginning to focus on virtual reality (VR) technology due to its ability to support immersive learning, teaching through simulation, and gamification of learning. These systems can deliver high-level multisensory learning experiences that are important in the teaching of many subjects, especially those involving abstract concepts or requiring spatial skills, such as organic chemistry. Haptic experiences with VR, however, remain a challenge. In addition, development has focused on general entertainment/gaming; VR systems in chemistry implement simulations of the chemistry laboratory and other advanced systems whereas those that support safe, game-like, immersive and multisensory learning of organic chemistry with haptics at pre-university education levels are scarce. We developed the VR Multisensory Classroom (VRMC) as an immersive learning environment within a VR head-mounted display, where learners employ hand movements to build hydrocarbon molecules and experience haptic feedback through gloves with built-in sensors and hand-tracking with the Leap Motion system. We report here the evaluation of the first prototype by learners from diverse backgrounds who reported on the ability of the VRMC to support high engagement, motivation, interest and organic chemistry learning as well as diverse learning styles. The VRMC is a novel VR classroom that supports immersive learning in molecular organic chemistry with haptics for multisensory learning.
... A study by Kanda et al. [12] using robots as peer English tutors shows different ways children interact with robots and can benefit from them. Long-term interaction studies by Tanaka et al. using QRIO [21] and Hyun et al. using iRobiQ [22], show the level of social interactions between the robot and children. Through these experiments, they provide guidelines for using robots as tutors in the classrooms. ...
This paper describes research aimed at supporting children's reading practices using a robot designed to interact with children as their reading companion. We use a learning by teaching scenario in which the robot has a similar or lower reading level compared to children, and needs help and extra practice to develop its reading skills. The interaction is structured with robot reading to the child and sometimes making mistakes as the robot is considered to be in the learning phase. Child corrects the robot by giving it instant feedbacks. To understand what kind of behavior can be more constructive to the interaction especially in helping the child, we evaluated the effect of a deictic gesture, namely pointing on the child's ability to find reading mistakes made by the robot. We designed three types of mistakes corresponding to different levels of reading mastery. We tested our system in a within-subject experiment with 16 children. We split children into a high and low reading proficiency even-though they were all beginners. For the high reading proficiency group, we observed that pointing gestures were beneficial for recognizing some types of mistakes that the robot made. For the earlier stage group of readers pointing were helping to find mistakes that were raised upon a mismatch between text and illustrations. However, surprisingly, for this same group of children, the deictic gestures were disturbing in recognizing mismatches between text and meaning.
... This entails that robots are more likely to be approached as (humanlike) artifacts to interact with, rather than to be used as tools for something else ( Höflich, 2013;van Oost & Reed, 2011;Zhao, 2006). Indeed, when the robotic tutor under study was implemented in a set of schools in Europe, it was evident that children were prone to interact with it socially ( ), or to perceive it as a friend ( Alves-Oliveira, Sequeira, & Paiva, 2016); findings that have been reported in other CRI studies, as well ( Fior, Nugent, Beran, Ramirez-Serrano, & Kuzyk, 2010;Hyun, Yoon, & Son, 2010;Kahn, Friedman, Perez-Granados, & Freier, 2004;Kanda, Hirano, Eaton, & Ishiguro, 2004;Kennedy, Baxter, & Belpaeme, 2015;Tanaka, Cicourel, & Movellan, 2007). On the other hand, robots are similar to other digital learning applications in the way that such tasks are usually structured. ...
In recent years, there has been a growing research interest towards exploring the benefit of Child–Robot Interaction for educational purposes through the use of social robotics. Despite the label, such robots are typically only social within scripted activities. The current study takes a critical look at the case of a robotic tutor which was implemented in an elementary school for 3.5 months, where children repeatedly took turns interacting with the robot individually as well as in pairs. The aim of the study was to explore what caused breakdowns in children's interactions with the robotic tutor. In this qualitative study, over 14 h of video recordings of children's interaction sessions were analyzed in-depth through interaction analysis and thematic analysis. The results comprise four themes to explain why children's interactions with the robotic tutor break down: (1) the robot's inability to evoke initial engagement and identify misunderstandings, (2) confusing scaffolding, (3) lack of consistency and fairness, and finally, (4) controller problems. The implications of these breakdowns for the educational use of robots are discussed, and it is concluded that several challenges need to be rigorously addressed in order for robotic tutors to be able to feature in education.
... Virtual agent based training has primarily been applied to educational learning where the agent interacts with the human throughout the training process.Virtual agent based teaching and feedback based learning environments have shown significantly better learning performance and a higher level of learner satisfaction.Experiments conducted with young children showed higher educational perception when automated agents were introduced into their traditional teaching environment [11]. ...
Soft skill assessment is a vital aspect of a job interview process as these qualities are indicative of the candidates compatibility in the work environment, their negotiation skills, client interaction prowess and leadership flair among other factors. The rise in popularity of asynchronous video based job interviews has created the need for a scalable solution to gauge candidate performance and hence we turn to automation.
In this research, we aim to build a system that automatically provides a summative feedback to candidates at the end of an interview. Most feedback system predicts values of social indicators and communication cues, leaving the interpretation open to the user. Our system directly predicts an actionable feedback that leaves the candidate with a tangible take away at the end of the interview. We approached placement trainers and made a list of most common feedback that is given during training and we attempt to predict them directly.
Towards this front,we captured data from over 145 participants in an interview like environment. Designing intelligent training environments for job interview preparation using a video data corpus is a demanding task due to its complex correlations and multimodal interactions. We used several state-of-the-art machine learning algorithms with manual annotation as ground truth. The predictive models were built with a focus on nonverbal communication cues so as to reduce the task of addressing the challenges faced in spoken language understanding and task modelling. We extracted audio and lexical features and our findings indicate a stronger correlation to audio and prosodic features in candidate assessment.Our best results gave an accuracy of 95% when the baseline accuracy was 77%.
... Robots are often intentionally designed to evoke children's relationship formation with them [7,12]. For example, Kanda, Sato, Saiwaki and Ishiguro [8] implemented strategic social behaviors in their classroom robot seeking to encourage more long-term interactions, and several studies have revealed tendencies in children to perceive robots as friends [27,[39][40][41]. Turkle [42] has observed that social robots evoke feelings of attachment in people, and argues that social robots are becoming relational artifacts. ...
As robots are becoming increasingly common in society and education, it is expected that autonomous and socially adaptive classroom robots may eventually be given responsible roles in primary education. In this paper, we present the results of a questionnaire study carried out with students enrolled in compulsory education in three European countries. The study aimed to explore students' normative perspectives on classroom robots pertaining to roles and responsibilities, student-robot relationships, and perceptive and emotional capabilities in robots. The results suggest that, although students are generally positive toward the existence of classroom robots, certain aspects are deemed more acceptable than others.
... Anthropomorphism, or ascription of agency, has consequences for relationships. Previous research has shown that children can perceive robots as friends (Fior et al. 2010;Hyun et al. 2010;Kanda et al. 2004;Tanaka et al. 2007), although robots are also seen as a separate ontological entity or ''hybrid being'' (Eunja et al. 2012;Kahn et al. 2013). Thus, although robots are not perceived to be completely human (Eunja et al. 2012), children nevertheless seem to project their understanding of humans onto robots, allowing friendships to form (Beran and Ramirez-Serrano 2011). ...
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.
... There are a number of facets of (social) robots that encourage interaction from the perspective of children. Further to the embodiment of the robot (as discussed above), the appearance of the robot embodiment itself can imply cognitive abilities (Turkle, Breazeal, Dasté, & Scassellati, 2006;Hyun & Son, 2010;Beran et al., 2011), thus extending the implied possible interaction beyond that typically achievable with toys. Whether related to this effect directly or not, there is some indication that children will comply with instructions or suggestions from a robot , and also tend to align their behaviour with that of the robot (Nalin, Baroni, Kruijff-Korbayova, et al., 2012) during an interaction. ...
Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.
... Recently, with the explosion of online learning, individualised and intelligent tutoring systems are gaining significant attention from different stakeholders. There have been some studies investigating the use of robotic tutors as a new interactive technology for learning [1], [2], [3]. In the EMOTE EU FP7 project 1 , we aim to build robots to be used in individual and collaborative learning scenarios [4], [5]. ...
There has been some studies in applying robots to education and recent research on socially intelligent robots show robots as partners that collaborate with people. On the other hand, serious games and interaction technologies have also proved to be important pedagogical tools, enhancing collaboration and interest in the learning process. This paper relates to the collaborative scenario in EMOTE EU FP7 project and its main goal is to develop and present the dialogue dimensions for a robotic tutor in a collaborative learning scenario grounded in human studies. Overall, seven dialogue dimensions between the teacher and students interaction were identified from data collected over 10 sessions of a collaborative serious game. Preliminary results regarding the teachers perspective of the students interaction suggest that student collaboration led to learning during the game. Besides, students seem to have learned a number of concepts as they played the game. We also present the protocol that was followed for the purposes of future data collection in human-human and human-robot interaction in similar scenarios.
... RUBI is a humanoid with articulated arms, an expressive face, and a tablet embedded in its midsection on which it displays educational content like vocabulary lessons. A study of the iRobiQ, a humanoid similar in design to RUBI, provides some experimentally-derived guidelines for using robot tutors in classrooms [8]. Research has also been done on tutoring robots that operate as museum guides [9] or teleoperated instruments of a human teacher, such as the Huggable robot [10]. ...
In education research, there is a widely-cited result called "Bloom's two sigma" that characterizes the differences in learning outcomes between students who receive one-on-one tutoring and those who receive traditional classroom instruction. Tutored students scored in the 95th percentile, or two sigmas above the mean, on average, compared to students who received traditional classroom instruction. In human-robot interaction research, however, there is relatively little work exploring the potential benefits of personalizing a robot's actions to an individual's strengths and weaknesses. In this study, participants solved grid-based logic puzzles with the help of a personalized or non-personalized robot tutor. Participants' puzzle solving times were compared between two non-personalized control conditions and two personalized conditions (n=80). Although the robot's personalizations were less sophisticated than what a human tutor can do, we still witnessed a "one-sigma" improvement (68th percentile) in post-tests between treatment and control groups. We present these results as evidence that even relatively simple personalizations can yield significant benefits in educational or assistive human-robot interactions.
Artificial Intelligence (AI) technologies have been applied in various domains, including early childhood education (ECE). Integration of AI educational technology is a recent significant trend in ECE. Currently, there are more and more studies of AI in ECE. To date, there is a lack of survey articles that discuss the studies of AI in ECE. In this paper, we provide an up-to-date and in-depth overview of the key AI technologies in ECE that provides a historical perspective, summarizes the representative works, outlines open questions, discuss the trends and challenges through a detailed bibliometric analysis, and provides insightful recommendations for future research. We mainly discuss the studies that apply AI-based robots and AI technologies to ECE, including improving the social interaction of children with an autism spectrum disorder. This paper significantly contributes to provide an up-to-date and in-depth survey that is suitable as introductory material for beginners to AI in ECE, as well as supplementary material for advanced users.
The purpose of this study was to explore the impact of several design factors on people’s perceptions of rendered robot faces. Experiment 1 was a 2 × 5 × 2 × 2 mixed 4-way ANOVA design. The research variables were head shape (round versus rectangular), facial features (baseline, cheeks, eyelids, no mouth and no pupils), camera (no camera versus camera), and participants’ gender (male versus female). Twenty static synthetic robot faces were created and presented to the participants. A total of 60 participants took part in the experiment through the online survey via the convenience sampling method. Experiment 2 was a 2 × 2 between-subjects 2-way design, the variables were the head shape (round versus rectangular) and camera (no camera versus camera). Four types of robot heads were created and presented to the participants during a real human–robot interaction. A total of 40 participants invited via the convenience sampling method conducted the experiment in a controlled room. The generated results are as follows: (1) A round robot’s head was considered more humanlike, as having more animacy, friendlier, more intelligent, and more feminine than a rectangular head. (2) No camera was considered to be friendlier. The round head with camera was considered more human-like and more intelligent than the head without a camera. (3) In the evaluation of the rendered robot faces, the female participants’ scores were more sensitive than those of the male participants. (4) The combination of a baseline face and a round head, no pupils or no mouth combined with a rectangular head might make the robot look more mature.
One of the main concerns of modern life would be the potential risk of irreversible ecological damage. However, due to the lack of focus on the subject within education, this type of risk will only get worse when being left unattended. This is where the robotics system, known as the “Smart Trashcan Brothers”, can provide better environmental consciousness with the current, younger generation attending primary school. This paper goes over the concepts that make up the Smart Trashcan Brothers system, as well with a functional evaluation to verify that the described parts of the robotics system function as intended. From there, a discussion of future works will be brought up with regards to further Child Human Interaction works.KeywordsRecycling robotSmart trash canTrash can robotHuman-robot interactionMachine learningImage processing
Robots have become an increasingly important part of our lives. They have been introduced in the education sector in the form of social robots with humanoid features that allow them to deliver lessons and interact with students. Despite the fact that research has shown that students aged 12 and below improve their learning when taught by robots and enjoy interacting with them, there are lingering concerns about their widespread use. The concerns include the lack of accountability, the impact of robots on normal socio-emotional development, and the dependence of robots on outside support. This research study aimed to assess the impact of increased awareness of the role of an assistant robot teacher in the classroom on the receptivity of high school students towards the inclusion of assistant robot teachers in the classroom. Specifically, the respondents were asked to rate their perceptions of the potential benefits of having an assistant robot teacher in the classroom before and after watching an informational video clip about an assistant robot teacher. The video clip features an Indian international school’s advocacy for the deployment of an assistant robot teacher. The results showed that the video clearly had a statistically positive impact on increasing the respondents’ receptivity towards having an assistant robot teacher. Based on the respondents’ responses, it is evident that they were clear about the strengths (vast knowledge repository, animation, graphics) and limitations (contextual response) of the robots.
Virtual Reality (VR) technology is fast becoming an everyday technology. It's specific ability in supporting a combination of immersive learning, teaching through simulation, and gamification of learning, holds significance for promoting high-level multi-sensory learning experiences that are important in the teaching of subjects, involving mastery of abstract concepts or spatial skills. The advantages can be immensely stepped up when integrated with haptics. Our VR Multisensory Classroom (VRMC) is an immersive chemistry classroom on HMD, where learners employ hand movements to build hydrocarbon molecules and experience haptic feedback. Evaluation of the first prototype shows the VRMC can support high engagement, motivation, interest and experiential learning.
With physical actions and digital effects conjoined, Augmented Reality technology generates the 'flow effect' (concentration) and encourages motivation. For this reason, there have been recent increases in the number of the studies looking at how AR can be applied to education. Similarly, we deployed a projector-robot at a kindergarten to support AR based dramatic plays by. In order for teachers to easily operate the projector-robot and manage its service, interactive flash-based augmented reality contents have been developed. The significance of the study is in that teachers are able to save time in preparing props for dramatic play classes, while students become more motivated and immersed. The proposed solution is relatively inexpensive and new services are easily added for wide adoption.
The purpose of this study is to examine how children perceived the use of intelligent service robots in early childhood education and identifying the characteristics of the interaction between the children concerned and the robots. The subjects of this study were 49 kindergarten students from Girin Kindergarten in Gyeonggi-do. The results of this study suggested that the children personalized the robot and recognized it as their friend, regardless of their ages. In the interactions between the children and the robot, the children engaged in physical contact with the robot and occasionally tried to control its functions. In the child-robot interaction, the children searched their favorite functions and used them repeatedly, but also lost interest in those repeated functions. Regardless of their interest levels, however, the attendance or portfolio organization functions. With regard to the interaction between peers, there were frequent quarrels regarding the use of the robot at first, but these conflicts were resolved by the intervention of peers or teachers, and the children who were familiar with the use of the robot helped their friends; this was viewed as constituting cooperative behavior. Children usually used the robot with their friends. The robot was a medium for children to find new friends. Peer group activities were explored and new friendships were created as a result of the use of the robot.
This paper describes a project-based learning case example developed at the University of Lleida, Spain. This proposal was addressed to third-year engineering students and combines knowledge from computer vision and robotic control to complete an automation project task. The learning target was to develop a computer vision system that must detect a small object placed randomly on a target surface and control an educational robotic arm to pick it up and move it to a predefined destination. The educational results of this experience have shown that the development of a practical-learning case based on the combination of computer vision and robotics has increased the motivation of the students and improved the assimilation of theoretical concepts.
For learning events that require a close collaboration and knowledge transfer between learners and intelligent tutoring agents, design specifications should be introduced. At the beginning of design, a learning methodology that supports collaborative and expletory construction of knowledge should be identified. In addition, the roles of intelligent tutoring agents should be assigned. This paper investigates the specific roles of intelligent tutoring agents to support dialectical learning strategy that enable learners' collaborative and autonomous exploration of knowledge. The Socratic Method is proposed as the dialectic learning method for autonomous exploration and collaboration for knowledge construction and a robotic tutor is proposed as the intelligent tutoring agent. This paper will be applicable for designing effective learning strategies for expletory and collaborative knowledge construction in autonomous ways and will be useful as a guideline for instructional designers, robot designers and teachers to understand the roles of intelligent tutoring agents in learning environments.
As the field of HRI evolves, it is important to understand how users interact with robots over long periods. This paper reviews the current research on long-term interaction between users and social robots. We describe the main features of these robots and highlight the main findings of the existing long-term studies. We also present a set of directions for future research and discuss some open issues that should be addressed in this field.
Takayuki Kanda is a computer scientist with interests in intelligent robots and human-robot interaction; he is a researcher in the Intelligent Robotics and Communication Laboratories at ATR (Advanced Telecommunications Re-search Institute), Kyoto, Japan. Takayuki Hirano is a computer scientist with an interest in human–robot interaction; he is an intern researcher in the Intelli-gent Robotics and Communication Laboratories at ATR, Kyoto, Japan. Daniel Eaton is a computer scientist with an interest in human–robot interaction; he is an intern researcher in the Intelligent Robotics and Communication Labora-tories at ATR, Kyoto, Japan. Hiroshi Ishiguro is a computer scientist with in-terests in computer vision and intelligent robots; he is Professor of Adaptive Machine Systems in the School of Engineering at Osaka University, Osaka, Ja-pan, and a visiting group leader in the Intelligent Robotics and Communication Laboratories at ATR, Kyoto, Japan. ABSTRACT Robots increasingly have the potential to interact with people in daily life. It is believed that, based on this ability, they will play an essential role in human society in the not-so-distant future. This article examined the proposition that robots could form relationships with children and that children might learn from robots as they learn from other children. In this article, this idea is studied in an 18-day field trial held at a Japanese elementary school. Two English-speak-ing "Robovie" robots interacted with first-and sixth-grade pupils at the perime-ter of their respective classrooms. Using wireless identification tags and sensors, these robots identified and interacted with children who came near them. The robots gestured and spoke English with the children, using a vocabulary of about 300 sentences for speaking and 50 words for recognition.
In this paper we describe a robotic game buddy whose emotional behaviour is influenced by the state of the game. Using the iCat robot and chess as the game scenario, an architecture for incorporating emotions as a result of a heuristic evaluation of the state of the game was developed. The game buddy was evaluated in two ways. First, we investigated the effects of the characterpsilas emotional behaviour on the userpsilas perception of the game state. And secondly we compared a robotic with a screen based version of the iCat in terms of their influence on userpsilas enjoyment. The results suggested that userpsilas perception of the game increases with the iCatpsilas emotional behaviour, and that the enjoyment is higher when interacting with the robotic version.
The goal of this article is to introduce the reader to the rich and vibrant field of robotics. Robotics is a field in change; the meaning of the term robot today differs substantially from the term just 1 decade ago. The primary purpose of this article ...