Towards Empathic Virtual and Robotic Tutors

Social Robots for (Second) Language Learning in (Migrant) Primary School Children

Especially these days, innovation and support from technology to relieve pressure in education is highly urgent. This study tested the potential advantage of a social robot over a tablet in (second) language learning on performance, engagement, and enjoyment. Shortages in primary education call for new technology solutions. Previous studies combined robots with tablets, to compensate for robot’s limitations, however, this study applied direct human–robot interaction. Primary school children (N = 63, aged 4–6) participated in a 3-wave field experiment with story-telling exercises, either with a semi-autonomous robot (without tablet, using WOz) or a tablet. Results showed increased learning gains over time when training with a social robot, compared to the tablet. Children who trained with a robot were more engaged in the story-telling task and enjoyed it more. Robot’s behavioral style (social or neutral) hardly differed overall, however, seems to vary for high versus low educational abilities. While social robots need sophistication before being implemented in schools, our study shows the potential of social robots as tutors in (second) language learning.

What Does It Mean to Empathise with a Robot?

Given that empathy allows people to form and maintain satisfying social relationships with other subjects, it is no surprise that this is one of the most studied phenomena in the area of human–robot interaction (HRI). But the fact that the term ‘empathy’ has strong social connotations raises a question: can it be applied to robots? Can we actually use social terms and explanations in relation to these inanimate machines? In this article, I analyse the range of uses of the term empathy in the field of HRI studies and social robotics, and consider the substantial, functional and relational positions on this issue. I focus on the relational (cooperational) perspective presented by Luisa Damiano and Paul Dumouchel, who interpret emotions (together with empathy) as being the result of affective coordination. I also reflect on the criteria that should be used to determine when, in such relations, we are dealing with actual empathy.

Exploring the Role of Perspective Taking in Educational Child-Robot Interaction

Perspective taking is an important skill to have and learn, which can be applied in many different domains and disciplines. While the ability to recognize other’s perspective develops in humans from childhood and solidifies during school years, it needs to be developed in robotic and artificial agents’ cognitive framework. In our quest to develop a cognitive model of perspective taking for agents and robots in educational contexts, we designed a task that requires the players (e.g., child and robot) to take the perspective of another, in order to complete and win the task successfully. In a preliminary study to test the system, we were able to evaluate children’s performance over four different age groups by focusing on their performance during the interaction with the robot. By analyzing children’s performance, we were able to make some assumptions about children’s understanding of the game and select the appropriate age group to participate in the main study.

Multi-party Turn-Taking in Repeated Human–Robot Interactions: An Interdisciplinary Evaluation

As social robots become more popular, so arises the need for these social agents to operate in environments involving multiple users. The robot control systems that govern these multi-party interactions require to be evaluated both from the technical and social standpoints. This paper presents the methodology, setup and results for experiment involving the social robot EMYS participating in multi-party interaction where pairs of participants interacted with the robot in a trivia questions game lead by the robot . In total 32 people, 16 pairs, interacted with the robot twice, which resulted in 32 interactions and 64 filled questionnaires. The developed robot’s multi-party interaction system was evaluated both in terms of performance and user assessment. The results show that the robot adhering to human turn-taking social norms reduced the number of occurring conversational errors, which improved the communicative performance from$$51.5\%$$51.5%to$$80.5\%$$80.5%, in addition, it made the robot perceived as more communicative, cooperative and fitting user expectations by up to 3 points on a 7 point scale. In addition, the study on repeated interactions revealed that user perception of the robot is affected by subsequent interactions, which can be of consequence in future experiments. This first impression caused lasting effect between 1 and 2 points on user assessment of several robot’s aspects, even when contradicted by objective performance measurement of the robot’s actual behavior.