A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> The scenarios and design process for a childcare robot, PaPeRo, are presented. The design process mainly consists of production and evaluations. The production is composed of three observations, namely, one in the user field, one with respect to the world view, and one about the assumed users and results for the basic role of the robot, its personality, and classification of users. Our investigation of available technologies deepened our understanding of the robot performance and characteristics. Preproduction, which consisted of a scenario design, prototyping, and a short play, made the scenario details more sophisticated. A six-month demonstration at the 2005 Aichi Expo started with seven different scenarios, which were improved using additional recognition words, more attractive robot personalities, and additional scenarios through on-site observations and discussion with staff members there. We conducted an extensive study on the robot personalities and recognizable words. Our study will play an important role in the scenario design process. <s> BIB001 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Advancement in robotic research enables robot can assist human in many way. However, few researches have been done on applying on education. This paper reports field trials of using robot in an English learning classroom. In our experiment, the robot plays as a partner of a teacher. Five models of collaboration between teachers and robot are proposed. Teachers design the course flow in advance based on the learning content and these five models. Formative evaluations of the experiments are presented to show the impact of adopting robot in the classroom. <s> BIB002 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> We are developing a storytelling robot which learns by children's teaching. The robot is used on learning of the second language. It can reduce the negative emotion due to the anxiety of speaking foreign language, which thus motivates learning and enhances the speaking and listening abilities. Presently, our system is still at the initial stage of research. Therefore, we only interviewed and experimented on some of the children now. These results will be used to improve our system. <s> BIB003 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> A number of studies on teaching assistant robots (or peer tutoring robots) have proven that robots can be considered effective tools for language education. Interactive storytelling, in particular, can be used for enhancing the teaching of English as a foreign language. This can be used in robot aided learning of English. However, the biggest obstacle to the interaction between human beings and robots in field studies is the robots’ low-success rate of face and voice recognition. This causes some children to utterly give up interaction with robots or to just ignore them altogether. This paper explores robot storytelling elements to look at ways of generating and maintaining interaction between teaching assistant robots and children. Robot storytelling about the robot’s own weak recognition was examined to see if it could address the challenge of changing children’s attitudes and maintain interaction between the children and the robot. It was concluded that teaching assistant robot storytelling is effective in increasing children’s tolerance towards robot weak recognition. <s> BIB004 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> This paper introduced a telepresence robot system for English tutoring. The system consists of the user system, the server system and the robot system. The robot is controlled by the collision prevention system, direct interface, server interface with assistant teacher and remote interface with native teacher. A remote native teacher had given lessons in English using this system for a month and several issues of telepresence robot system for remote lecture are found from the lecture. <s> BIB005 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> The main aim of the modern popular teaching method of authentic learning has been to provide students with everyday-life challenges that develop knowledge and skills through problem solving in different situations. Many emerging information technologies have been used to present authentic environment in pedagogical purpose. However, there are few studies that have been discussed the sense of authenticity and characters in scene and how students interact with the characters involved in the task. We designed a system, RoboStage, with authentic scenes by using mixed-reality technology and robot to investigate the difference in learning with either physical or virtual characters and learning behaviors and performance through the system. Robots were designed to play real interactive characters in the task. The experiment of the study conducted with 36 junior high students. The results indicated that RoboStage significantly improved the sense of authenticity of the task and also positively affected learning motivation. Learning performance was conditionally affected by RoboStage. <s> BIB006 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Teaching is inherently a social interaction between teacher and student. Despite this knowledge, many educational tools, such as vocabulary training programs, still model the interaction in a tutoring scenario as unidirectional knowledge transfer rather than a social dialog. Therefore, ongoing research aims to develop virtual agents as more appropriate media in education. Virtual agents can induce the perception of a life-like social interaction partner that communicates through natural modalities such as speech, gestures and emotional expressions. This effect can be additionally enhanced with a physical robotic embodiment. This paper presents the development of social supportive behaviors for a robotic tutor to be used in a language learning application. The effect of these behaviors on the learning performance of students was evaluated. The results support that employing social supportive behavior increases learning efficiency of students. <s> BIB007 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Various studies on robot assisted learning have proven them to be effective tools for language education because robots are remarkably successful in eliminating the affective filter. This study demonstrates ROBOSEM with class content for sustaining long-term interaction with students in English classes of elementary schools as a teaching assistant, not a teacher. We close with some practical considerations for the continuous process of improving technology and its diffusion throughout society, such as in elementary schools, through interviews with developers and observations from field trials. <s> BIB008 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> In this study, the researchers attempted to extend the concept of learning companions from the virtual world to the real physical environment and made a breakthrough in technique development of tangible learning robots. The aim of this study was to explore an innovative way by combining the speech recognition technology with educational robots in the hope that the state-of-the-art technology could provide learners with more opportunities of bi-directional language learning in the English class settings. The quasi-experimental design was adopted in this study and a total of 63 Taiwanese students in the fifth grade participated in the experiment. The results reveal that using the tangible learning companions in learning had positive effects on learners' learning motivation, confidence and engagement especially for the lower-achievement learners. Two learning methods were identified in the study, co-discovery and peer tutoring method. The co-discovery method enhanced the lower-achievement learners' learning involvement and their English speaking ability. Students perceived the tangible learning robots as friendly learning toys or ever like a patient instructor for practicing English conversation. Both English instructor and students agreed that uses of the tangible learning companions effectively improved the class atmosphere, and raised their and positive attitude toward learning English. <s> BIB009 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> In contrast to conventional teaching agents (including robots) that were designed to play the role of human teachers or caregivers, we propose the opposite scenario in which robots receive instruction or care from children. We hypothesize that by using this care-receiving robot, we may construct a new educational framework whose goal is to promote children's spontaneous learning by teaching through their teaching the robot. In this paper, we describe the introduction of a care-receiving robot into a classroom at an English language school for Japanese children (3--6 years of age) and then conduct an experiment to evaluate if the care-receiving robot can promote their learning using English verbs. The results suggest that the idea of a care-receiving robot is feasible and that the robot can help children learn new English verbs efficiently. In addition, we report on investigations into several forms of teaching performed by children, which were revealed through observations of the children, parent interviews, and other useful knowledge. These can be used to improve the design of care-receiving robots for educational purposes. <s> BIB010 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> A robot-based English curriculum called The Missing Code has been developed to teach English vocabulary to young children whose home language is one other than English. Guided by theories in children’s learning and motivation, the curriculum was designed to be developmentally appropriate and engaging for children who were 3-5 years old, carefully balancing the familiar and the new. The development process was characterized by iterative cycles of initial design, user testing, and refinement. Through multiple observations of child-robot play in situ, it was noted that children easily learned how to interact with the robot and showed sustained interest and engagement in the curricular activities with the robot. 뀀ഀȠ 뀀ഀȠ <s> BIB011 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> This paper investigates the role of interaction and communication kinesics in human–robot interaction. This study is part of a novel research project on sign language (SL) tutoring through interaction games with humanoid robots. The main goal is to motivate the children with communication problems to understand and imitate the signs implemented by the robot using basic upper torso gestures and sound. We present an empirical and exploratory study investigating the effect of basic nonverbal gestures consisting of hand movements, body and face gestures expressed by a humanoid robot, and having comprehended the word, the participants will give relevant feedback in SL. This way the participant is both a passive observer and an active imitator throughout the learning process in different phases of the game. A five-fingered R3 robot platform and a three-fingered Nao H-25 robot are employed within the games. Vision-, sound-, touch- and motion-based cues are used for multimodal communication between the robot, child and therapist/parent within the study. This paper presents the preliminary results of the proposed game tested with adult participants. The aim is to evaluate the SL learning ability of participants from a robot, and compare different robot platforms within this setup. <s> BIB012 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> This paper presents a design for a cutting-edge English program in which elementary school learners of English as a foreign language in Taiwan had lively interactions with a teaching assistant robot. Three dimensions involved in the design included (1) a pleasant and interactive classroom environment as the learning context, (2) a teaching assistant robot designed and built by the researchers as instructional technology (instructional tool/medium), and (3) the need for improved motivation and learning outcomes and positive learning experiences of the students as the core research problem. This Human–Robot Interaction (HRI) led to better pedagogical effects on learning and teaching by (1) employing a vivid, enjoyable teaching approach; (2) adopting practical, interesting learning materials; and (3) creating a natural, enjoyable learning context. Both quantitative and qualitative findings of this study indicate that the students' English learning experiences were enhanced, as were their motivation and learn... <s> BIB013 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Curiosity is key to learning, yet school children show wide variability in their eagerness to acquire information. Recent research suggests that other people have a strong influence on children’s exploratory behavior. Would a curious robot elicit children’s exploration and the desire to find out new things? In order to answer this question we designed a novel experimental paradigm in which a child plays an education tablet app with an autonomous social robot, which is portrayed as a younger peer. We manipulated the robot’s behavior to be either curiosity-driven or not and measured the child’s curiosity after the interaction. We show that some of the child’s curiosity measures are significantly higher after interacting with a curious robot, compared to a non-curious one, while others do not. These results suggest that interacting with an autonomous social curious robot can selectively guide and promote children’s curiosity. Categories and Subject Descriptors K.3.1 [Computers and Education]: Computer Uses in Education; I.2.9 [Artificial Intelligence]: Robotics <s> BIB014 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Effective tutoring requires personalization of the interaction to each student. Continuous and efficient assessment of the student's skills are a prerequisite for such personalization. We developed a Bayesian active-learning algorithm that continuously and efficiently assesses a child's word-reading skills and implemented it in a social robot. We then developed an integrated experimental paradigm in which a child plays a novel story-creation tablet game with the robot. The robot is portrayed as a younger peer who wishes to learn to read, framing the assessment of the child's word-reading skills as well as empowering the child. We show that our algorithm results in an accurate representation of the child's word-reading skills for a large age range, 4-8 year old children, and large initial reading skill range. We also show that employing child-specific assessment-based tutoring results in an age- and initial reading skill-independent learning, compared to random tutoring. Finally, our integrated system enables us to show that implementing the same learning algorithm on the robot's reading skills results in knowledge that is comparable to what the child thinks the robot has learned. The child's perception of the robot's knowledge is age-dependent and may facilitate an indirect assessment of the development of theory-of-mind. <s> BIB015 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Computer assisted language learning (CALL) is going to be more attractive, more interactive and more realistic by introducing humanoid robots. We propose a novel joining-in type robot assisted language learning (RALL) system using two humanoid robots, one playing a role of a teacher and the other playing a role of an advanced learner. The system has a seamless scenario of a natural dialogue flow among two robots and a learner to draw the learner into the dialogue. We designed the system to switch two modes of learning: tutoring and peer learning. As a characteristic behavior of the peer learning, we expect an “alignment” phenomenon between the robot's sample answer and the learner's utterance. That is to say, the learner learns a sentence pattern by mimicking a sample answer presented by the advanced learner robot. We created a learner corpus of over 60 participants, carried out an analysis on how much alignment occurred in the interactions. <s> BIB016 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Introduction Anthropomorphized robots are found beneficial when they are implemented in education due to their advantages of executing verbal and nonverbal communication with teachers or students in classrooms (Johnson, 2003). For example, some research studies have used autonomous humanoid robots in English classrooms to play the role of native speakers that are able to carry on conversations with pupils in natural language (Lee et al., 2011; Hyun et al., 2008; Movellan et al., 2009; Park et al., 2011). Research studies have confirmed that this type of interaction between robots and humans not only improves teaching effectiveness but also learning motivation because students are less anxious and more cheerful (Papert, 1993). Therefore, more and more applications of robotic technology are now trying to develop activities that can be helpful for teaching and learning English as a foreign language (EFL). This current trend of using robotics to assist language instruction is now known as Robot-Assisted Language Learning (RALL) (Han, 2012). Despite the great benefits of using robots in language teaching and learning, the current application may be limited because of the two major reasons. First, autonomous robots have complex artificial intelligence and are so expensive that normally schools cannot afford them. Moreover, the interaction scenarios between pupils and robots must be pre-programmed by robotics developers, so educators who are not robotics professionals may find it difficult to design or alter the interaction scenarios. Therefore, an alternative to solving the above problems is to buy robots with simple autonomous functions and remote controlled body movements from the supermarkets, or toyshops. These robots are mostly developed in a small size and at a low-cost. Meanwhile, they could be simply controlled by instructors to perform pedagogical missions and teaching materials in the classroom activities. This type of robots is often used as an instructional tool for facilitating learners' engagement and oral interaction. Research has found that interacting with a tangible robot increased more engagement than with a video (Xie, Antle, & Motamedi, 2008). For instance, ROBOSAPIEN, a low-cost remote controlled robot that can be purchased from a toyshop, has been used to be an instructional tool for EFL class at an elementary school (Chang et al., 2010a; Chang et al., 2010b; You et al., 2006). Although there was a breakthrough in terms of reducing the cost of using robots in language teaching and learning, those commercial robots were still not well developed into education because normally instructors had to take much time and effort to interlink robots with instructional materials and classroom activities. In order to expand robot-assisted language teaching, Han (2012) suggested that the system frameworks of RALL combine robot hardware, robot applications and visual instructional contents and help instructors easily design their robot-assisted instruction. Furthermore, the design of the system frameworks should take the language learning goals into account. In our previous research studies, a RALL system framework has been implemented. The developed framework provides an authoring tool for instructors to script teaching materials that can easily add external multimedia resources as well as to script presentations of anthropomorphized robots. Moreover, a material display system can also be found in the framework. Therefore, the present study is, first, to provide a practical study of creating an EFL course using the framework to design robot-assisted instructional materials. Then, it shows the empirical evidence of the designed instructional materials based on students' learning outcomes. Finally, it presents the impact of students' learning motivation because motivation is a critical element to sustain students' attention and engagement in the learning process. In our current study, two groups of the fifth-grade elementary students were targeted to make the comparison. … <s> BIB017 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> The CoWriter activity involves a child in a rich and complex interaction where he has to teach handwriting to a robot. The robot must convince the child it needs his help and it actually learns from his lessons. To keep the child engaged, the robot must learn at the right rate, not too fast otherwise the kid will have no opportunity for improving his skills and not too slow otherwise he may loose trust in his ability to improve the robot' skills. We tested this approach in real pedagogic/therapeutic contexts with children in difficulty over repeated long sessions (40-60 min). Through 3 different case studies, we explored and refined experimental designs and algorithms in order for the robot to adapt to the troubles of each child and to promote their motivation and self confidence. We report positive observations, suggesting commitment of children to help the robot, and their comprehension that they were good enough to be teachers, overcoming their initial low confidence with handwriting. <s> BIB018 </s> A Survey of Robot-Assisted Language Learning (RALL) <s> Social Role <s> Teaching with robots is a developing field, wherein one major challenge is creating lesson plans to be taught by a robot. We introduce a novel strategy for generating lesson material, in which we draw upon an existing corpus of electronic lesson material and develop a mapping from the original material to the robot lesson, thereby greatly reducing the time and effort required to create robot lessons. We present a system, KubiLingo, in which we implement content mapping for language lessons. With permission, we use Duolingo as the source of our content. In a study with 24 users, we demonstrate that user performance improves by a statistically similar amount with a robot lesson as with Duolingo lesson. We find that KubiLingo is more distracting and less likeable than Duolingo, indicating the need for improvements to the robot’s design. <s> BIB019
Robots used in language learning can exhibit one of four social roles: (1) teacher, (2) teacher's assistant, (3) peer/tutor, or (4) learner. Alternatively, they may not be classified as a social other at all. When assigned the role of teacher, teacher's assistant, or peer, knowledge transfer may be unidirectional, from the robot to the student, or bidirectional. However, these roles vary in intended levels of authority and connectedness with the student, with the teacher role being particularly high in authority and the peer/tutor role being particularly high in connectedness. In the learner role, knowledge transfer is mostly unidirectional, from the student to the robot. The role of teacher is used infrequently in RALL. In fact, educators have expressed discomfort with robots that are meant to be teachers, viewing them as intimidating BIB001 or competitors BIB008 . According to Osada et al., educators expressed that robots in the teacher role would face barriers to acceptance within the field BIB001 . Therefore, the teacher role is most commonly seen with telepresence robots, where a live teacher is present, as seen with References BIB005 and  . However, studies have also explored using two robots in conjunction to improve outcomes, with one robot meant to function as the teacher to another less advanced robot BIB016  . After watching both robots interact, the robot in the teacher role would ask the human learner questions. This was meant to serve as a conversational model from which the human could draw. Autonomous robots acting as teacher's assistants does occur BIB017 BIB013 . For instance, Hong et al. gave Bioloid the role of teacher's assistant, having it give students commands and assign them tasks BIB017 . Likewise, the PET robot was used to teach students the alphabet and instruct them to repeat sentences after it BIB013 . The inclusion of robots as teaching assistants may have a positive impact on students' learning when used in addition to human instructors, as they can serve to lower the affective filter (see Section 5-Results on Affective Changes of Learners). As the robot is subordinate to the human instructor, this role is more likely to be accepted among educators compared with robots meant to be teachers. It is, in practice, the only choice when attempting to use autonomous robots in a teaching role in classroom settings, due to the technical limitations and malfunctions of such technology in an environment that demands flexibility, stability, and control. The role of peer is seen more regularly (e.g., References BIB006 BIB011 ). This can take the form of tutoring or co-learning. The tendency is for children to describe robots in this position as more of a friend than a teacher (e.g., References BIB007  ). Due to the use of higher degrees of connectedness between the student and robot, learners tend to find this role highly desirable BIB007  , which may speak to the popularity of using robots in this way. Peer/tutor robots are used in both group and one-on-one instruction. Robots in the learner role take advantage of the care-receiving paradigm (e.g., References BIB014 BIB010 BIB002 ). Prototypically, the robot is younger, smaller, and less knowledgeable than the student. There are a few reasons this role might be advantageous, such as when voice synthesis is not clear and students need to be comfortable expressing lack of understanding BIB015 , when voice recognition is weak and it is desirable to increase students' tolerance of this issue BIB004 , or to negate other mistakes without affecting the relationship BIB002 . In addition, this role has been utilized with the expectation that it will positively affect task motivation BIB018 BIB010 . Robots can also fail to invoke any social role. Broadly speaking, there are two reasons this might occur. First, this may be somewhat accidental, with students simply failing to classify it within the social hierarchy. For example, in Kose et al., children described NAO as a toy, while describing Robovie, a larger robot with the same role as NAO, as a peer BIB012 . This highlights that whether an agent is considered a social other may be independent from its actions. Further, it can be dependent on the group. In Chang, Lee, Wang et al. students seemed to treat the robot as a social other, while teachers failed to classify it as such, instead describing it as a tool BIB006 . To a lesser extent, this may also be dependent on the individual. In Wang, Young, and Jang, some students described Rocky as a peer or friend, while others labelled it a toy or doll BIB009 . Second, the lack of social role can be purposeful, as the robot is meant to function only as a tool (e.g., References BIB003 BIB019  ). According to Mubin et al., "the verbal articulations of the students had a direct influence on the Mindstorms robot, therefore we can hypothesize that the role of a tool for a robot might be better than the role of a peer, especially when it comes to language learning" [73:13] . This aligns with TPR theory (discussed in Section 6.4, Instructional Methods), which emphasizes a connection between learning and movement. Chang, Lee, Wang, and Chen also saw that children learned words used to control the robot better than words used within the learning task, though the task necessitated that they use these words at a much higher frequency BIB006 . There has been no research in RALL to indicate which social role is the best for language learning, or whether a social role should be utilized at all. It is conceivable that this would vary by type of language learning (comprehension vs expression), level (beginner vs intermediate vs advanced), and time (short vs long-term).