Children have been documented extending prosocial ideals and moral worth towards robots. However, there is also emerging evidence that children will behave violently towards robots. Given expectations that robots will soon become common fixtures in classrooms, and that children can behave violently towards robots, it is important that we identify how others might appraise the victims (robots) and perpetrators (children) of these scenarios. It is critical that we understand whether children will think it is okay to behave immorally towards a robot, or if they will be deterred by these acts of abuse. Additionally, we must determine how this will influence children's learning decisions. The proposed study aims to address these questions by creating a novel paradigm where children are asked to rate robots and humans who have been involved in a transgression, where the human behaves anti-socially towards the robot. This study will also aim to understand how these appraisals will influence childrens learning decisions in a forced choice, selective learning task.

Robots that facilitate touch by children have special requirements in terms of safety and robustness, but little is known about how and when children actually use touch with robots. Tools and techniques are required to sense the variety of children's touch and to interpret the volumes of data generated. This explorative user study investigated children's patterns of touch during game play with a robot. We examined where the children touch the robot and their patterns of touch over time, using a raster-based visualisation of each child's time series of touches, recording patterns of touch across different games and children. We found that children readily engage with the robot, in particular spontaneously touching the robot's hands more than any other area. This user study and the tools developed may aid future designs of robots to autonomously detect when they have been touched.