Summary: Young children are better able to understand what they are studying when they learn alongside a social robot.
Source: University of Twente
Research has shown that explaining aloud what you are learning, whether to yourself or to someone else, leads to a better understanding of the subject. But in situations where you are working independently, it is not particularly intuitive to start explaining things. Researchers at the University of Twente have discovered that primary school children can better explain what they are studying when they learn alongside a robot. Frances Wijnen, one of the ELAN researchers involved: “The results led us to conclude that social robots have the potential to support children’s learning in a new and positive way.”
Wijnen explains that a social robot is able to help a child to explain aloud what they are learning, even when no-one else is around. “In our study, we used the ZENO robot, which can show all sorts of facial expressions, wave, see and talk. ZENO’s social behaviours mean that it can trigger social reactions in people.”
The results of the study showed that when they had the robot for company, children spent more time explaining, mentioned more relevant information, and made more links between relevant pieces of information. “This is interesting,” says Frances, “because in both situations – one with the ZENO robot, and one with a tablet – the task and the interactions were the same.” In both settings, the children were able to give verbal explanations, and the robot and the tablet reacted in the same way; but the children who worked alongside the robot gave more detailed and complete explanations, indicating that they had understood the subject better.
More research is required to determine which aspects of the robot motivated the children to give better explanations. In any event, the results indicate that social robots have the potential to support children’s learning in a new and positive way.
RESEARCH STUDY DESIGN
To determine whether a social robot was better able to motivate children to explain what they were learning, two situations were compared. In the ‘control situation’, the children worked with a computer system controlled by a tablet. In the ‘experimental situation’, the children worked with the same computer system, supplemented by the ZENO robot. The participating children were given a learning task which required them to understand the operation of equilibrium, using a balance beam. The children could place pots of various weights on this balance beam, at various distances from the midpoint of the beam. Depending on the group they were in, the children were then asked to explain their findings either to the tablet or to the ZENO robot.
About this robotics research article
Source: University of Twente Media Contacts: L.P.W. Van Der Velde – University of Twente Image Source: The image is in the public domain.
Now We’re Talking: Learning by Explaining Your Reasoning to a Social Robot
This article presents a study in which we explored the effect of a social robot on the explanatory behavior of children (aged 6–10) while working on an inquiry learning task. In a comparative experiment, we offered children either a baseline Computer Aided Learning (CAL) system or the same CAL system that was supplemented with a social robot to verbally explain their thoughts to. Results indicate that when children made observations in an inquiry learning context, the robot was better able to trigger elaborate explanatory behavior. First, this is shown by a longer duration of explanatory utterances by children who worked with the robot compared to the baseline CAL system. Second, a content analysis of the explanations indicated that children who worked with the robot included more relevant utterances about the task in their explanation. Third, the content analysis shows that children made more logical associations between relevant facets in their explanations when they explained to a robot compared to a baseline CAL system. These results show that social robots that are used as extensions to CAL systems may be beneficial for triggering explanatory behavior in children, which is associated with deeper learning.