Social robots for education: A review <s> INTRODUCTION <s> Numerous studies have evaluated the effects of pedagogical agents on students’ learning outcomes, but so far, beneficial effects have not been consistently demonstrated. The ambiguous results might partly be due to the strong emphasis on cognitive outcomes, which is characteristic for research in teaching and learning. The paper suggests a shift of attention to socio-emotional and relational variables, which might be considered as relevant moderator variables in learning or even as learning outcomes per se, for example, in social learning. In order to achieve this goal, we suggest a systematic account of the results from social psychology and in particular from nonverbal communication research, and findings from studies on the social effects of embodied agents in general. This perspective will include (1) a distinction between static and dynamic aspects of embodiment, such as the visual appearance of agents and their nonverbal behavior, and (2) a more systematic approach concerning the functions of embodiment and nonverbal behavior, such as modeling, discourse and dialogue functions, and socio-emotional effects. A further argument addresses the necessity of complementing outcome measures by process measures, which are sensitive to the tasks and the changing situational demands that occur during learning processes and tutor-learner interaction. <s> BIB001 </s> Social robots for education: A review <s> INTRODUCTION <s> To date, there have been many studies that have deployed robots as learning and teaching assistants in educational settings to investigate their pedagogical effects on learning and teaching. Hendler (2000) categorized the robots with which learners may interact in the future into five categories, i.e., toy robotics, pet robotics, interactive displays, service robotics including assistive ones, and educational robotics. Goodrich and Schultz (2007) classified the educational service robots into assistive and educational robotics. The robots that can serve for educational purposes can be divided into two categories: educational robotics (also referred to as hands-on robotics), and educational service robotics. The difference between these two types of robotics stems from the primary user groups. Educational robotics has been used by prosumers, a blend of producers and consumers, while educational service robots show a clear boundary between the producers and consumers. In general, the latter takes anthropomorphized forms to substitute or support teachers. It can also add more than what computers have offered to aid language learning because their anthropomorphic figures lower the affective filter and provide Total Physical Response (TPR) in terms of actions, which may lead to form social interactions. This chapter focuses on educational service robots. Taylor (1980) emphasized that computers have played important roles as educational tutors, tools and tutees. It seems that educational service robots can act as emotional tutors, tutoring assistants (teaching assistants), and peer tutors. The tutor or teaching assistant robots can also be a kind of assistant for innovative educational technologies for blended learning in order to obtain the knowledge and skills under the supervision and support of the teacher inside and outside the classroom. Examples of this include computers, mobile phones, Sky TV or IP TV channels and other electronics. The studies of Mishra and Koehler (2006) probed into teachers’ knowledge, building on the idea of Pedagogical Content Knowledge (PCK) suggested by Shulman (1987). They extended PCK to consider the necessary relationship between technology and teachers’ subject knowledge and pedagogy, and called this Technological Pedagogical Content Knowledge (TPCK), as shown in Fig. 3. An educational service robot as a teaching and learning assistant for blended learning is divided into three categories: the tele-operated (or tele-conference, tele-presence) type, autonomous type, and transforming type, according to the location of TPCK, as displayed in Table 1. Source: Human-Robot Interaction, Book edited by: Daisuke Chugo, ISBN 978-953-307-051-3, pp. 288, February 2010, INTECH, Croatia, downloaded from SCIYO.COM <s> BIB002 </s> Social robots for education: A review <s> INTRODUCTION <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> BIB003 </s> Social robots for education: A review <s> INTRODUCTION <s> 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. <s> BIB004 </s> Social robots for education: A review <s> INTRODUCTION <s> This review describes a meta-analysis of findings from 50 controlled evaluations of intelligent computer tutoring systems. The median effect of intelligent tutoring in the 50 evaluations was to raise test scores 0.66 standard deviations over conventional levels, or from the 50th to the 75th percentile. However, the amount of improvement found in an evaluation depended to a great extent on whether improvement was measured on locally developed or standardized tests, suggesting that alignment of test and instructional objectives is a critical determinant of evaluation results. The review also describes findings from two groups of evaluations that did not meet all of the selection requirements for the meta-analysis: six evaluations with nonconventional control groups and four with flawed implementations of intelligent tutoring systems. Intelligent tutoring effects in these evaluations were small, suggesting that evaluation results are also affected by the nature of control treatments and the adequacy of progr... <s> BIB005
Virtual pedagogical agents and intelligent tutoring systems (ITSs) have been used for many years to deliver education, with comprehensive reviews available for each field BIB001 BIB005 . The use of social robots has recently been explored in the educational domain, with the expectation of similarly positive benefits for learners   BIB003 . A recent survey of long-term human-robot interaction (HRI) highlighted the increasing popularity of using social robots in educational environments BIB004 , and restricted surveys have previously been conducted in this domain BIB002  . In this paper, we present a review of social robots used in education. The scope was limited to robots that were intended to deliver the learning experience through social interaction with learners, as opposed to robots that were used as pedagogical tools for science, technology, engineering, and math (STEM) education. We identified three key research questions: How effective are robot tutors at achieving learning outcomes? What is the contribution made by the robot's appearance and behavior? And what are the potential roles of a robot in an educational setting? We support our review with data gleaned from a statistical meta-analysis of published literature. We aim to provide a platform for researchers to build on by highlighting the expected outcomes of using robots to deliver education and by suggesting directions for future research.