Trust is fundamental in Human-Robot Interaction (HRI) and can be influenced by factors such as the robot’s appearance, and texture. Research suggests that children can develop trust with robots, particularly humanoid ones; however, other studies raise concerns about robotic behaviors and the extent to which they are perceived as trustworthy. In this study, we investigate whether the co-designing of clothes for a Socially Assistive Robot (SAR) affects their trust in the SAR, specifically the Nao robot. Children aged 7-10 in small group workshops created with the needle felting technique clothes for Nao, guided by the robot itself and an expert. Each child made their own piece of clothing. Their a) trust, b) empathy, c) perceived liveliness, and d) negative attitudes before and after making the clothes were assessed with pre-post questionnaires, indicating a significant increase in trust and empathy. After making the clothes, each child interacted alone with 3 Nao robots; one with default appearance, one dressed in the clothes they made, and one with other similar clothes, and were invited to share a secret wish with one of them. Behavioral observations, individual interviews and linguistic analysis of the wishes, provided insights into factors influencing children’s trust and appearance preferences in HRI. Results indicated that most children chose to confide in the robot who wore their crafted outfit, expressing personal desires grammatically with the verb ’wish’ in contrast to the children who shared immediate desires with the verb ’want’ and chose the default robot. Finally, interviews indicated that the primary characteristics that make a SAR trustworthy to children are kindness, intelligence, anthropomorphism, and helpfulness.

Traffic safety education is the key to safe road behavior and can prevent severe and fatal accidents, and it is suggested starting from an early age. Technologies such as Augmented Reality (AR) and Socially Assistive Robots (SAR) have been successfully used in the last years in the educational field. Therefore, it is essential to identify how social robots and AR educational tools can be optimally used to support traffic safety education. In this paper, we introduce the idea of an educational approach with the combination of SAR with AR technologies to teach traffic safety in kindergarten. We have been inspired by evidence from human-robot interaction studies, suggesting both technologies can enhance gained knowledge using the storytelling method at an early age and trigger positive attitudes in the students after interacting with them. Our educational approach was benchmarked against a single AR application. Our study initially proved, through real-world experiments, that the combination of SAR and AR was successfully used to teach kindergarten students about traffic safety. It managed to sustain their attention for statistically significantly more time than the case of the single AR application. Students taught by the single AR application also managed to gain basic knowledge regarding traffic safety. Moreover, another important outcome of our study is that students improved their attitudes and beliefs regarding using SAR in education after interacting with it, as demonstrated by individual interviews. Hence, our results suggest that both AR applications and SAR are suitable for learning purposes in kindergarten, while the employment of SAR in AR educational applications sustains the students’ attention.

The development of technology in recent years has led to the research of innovative tools in education. Technologies, such as Augmented, Virtual, and Mixed Reality can be utilized in immersive environments for educational purposes. Educational Robotics has also been prevalent in K-12 and STEM education. In this paper, we describe a mobile augmented reality learning environment to support robotics programming. An augmented reality application was developed and evaluated by two experts. Two experiments were conducted, including the non-AR and the AR condition. The participants were primary school students. Both observation and interviews were conducted. Our results showed that augmented reality attracts students’ interest in robotics programming, prompts them to participate in the learning process and is easy to use. Limitations and advantages of the AR approach in educational robotics were pointed out. The results indicate that contextualizing robotics with augmented reality is promising and should be further studied.

In the coming years, social robots will be widely used in the educational field. Therefore, it is important to identify the future educators’ attitudes towards the use of robots and technological tools. In this paper, we investigate how the exposure of students/pre-service teachers in a robot-tutor can affect their attitudes towards the use of robots in education. We compare a university professor with a robot-tutor in a university class and we demonstrate how each one changes the students’ attitudes towards the use of robots and technology in education as well as the students learning outcome from the course. Furthermore, based on the results of the four experiments we conducted, we also demonstrate the changes in students’ attitudes when they have just a single lesson with a robot-tutor and when they have two courses. Our results demonstrate all students were more positive about the use of robots (and technology) in education after having a course with the robot-tutor than when they had a lecture with a human. Moreover, they had a similar knowledge acquisition level, as indicated by the given knowledge test in both human and robot-tutor conditions. Especially in the case that they had a second lecture with the robot-tutor, they got statistically significantly higher scores in the test in comparison with those who had only one lecture. Our results suggest that a robot-tutor can be an effective tutor, capable of changing students’ attitudes and improving knowledge. Moreover, since the university students in our experiments were pre-service teachers, our paper can act as a reference for teaching, the next generation of teachers, that a robot-tutor can be a useful colleague.

Scholars have highlighted the importance of the humanoid appearance and the integration of various social cues for the design of Socially Assistive Robots for Education (SAR). However, designing a SAR for education omitting the stakeholders that will exploit it might prove a risky task. The aim of the current study, on the one hand, was to present the design of a SAR for Science Technology Engineering and Mathematics (STEM) education developed through stakeholders' involvement in various steps of the approach. On the other hand, the study aimed to present the evaluation of the prototype robot through a STEM-oriented robot-assisted collaborative online teaching-learning sequence. Preliminary results indicate that participants endorsed the appearance and non-verbal behavior of the robot above chance level, while gender and age-related differences were revealed regarding the most appealing feature of the robot. Implications for Human-Robot Interaction are discussed.