How people talk when teaching a robot

We examine affective vocalizations provided by human teach-ers to robotic learners. In unscripted one-on-one interac-tions, participants provided vocal input to a robotic dinosaur as the robot selected toy buildings to knock down. We find that (1) people vary their vocal input depending on the learner’s performance history, (2) people do not wait until a robotic learner completes an action before they provide in-put and (3) people näıvely and spontaneously use intensely affective vocalizations. Our findings suggest modifications may be needed to traditional machine learning models to better fit observed human tendencies. Our observations of human behavior contradict the popular assumptions made by machine learning algorithms (in particular, reinforcement learning) that the reward function is stationary and path-independent for social learning interactions. We also propose an interaction taxonomy that describes three phases of a human-teacher’s vocalizations: direction, spoken before an action is taken; guidance, spoken as the learner communicates an intended action; and feedback, spo-ken in response to a completed action

When Children Teach a Robot to Write: An Autonomous Teachable Humanoid Which Uses Simulated Handwriting

This article presents a novel robotic partner which children can teach handwriting. The system relies on the learning by teaching paradigm to build an interaction, so as to stimulate meta-cognition, empathy and increased self-esteem in the child user. We hypothesise that use of a humanoid robot in such a system could not just engage an unmotivated student, but could also present the opportunity for children to experience physically-induced benefits encountered during human-led handwriting interventions, such as motor mimicry. By leveraging simulated handwriting on a synchronised tablet display, a nao humanoid robot with limited fine motor capabilities has been configured as a suitably embodied handwriting partner. Statistical shape models derived from principal component analysis of a dataset of adult-written letter trajectories allow the robot to draw purposefully deformed letters. By incorporating feedback from user demonstrations, the system is then able to learn the optimal parameters for the appropriate shape models. Preliminary in situ studies have been conducted with primary school classes to obtain insight into children’s use of the novel system. Children aged 6-8 successfully engaged with the robot and improved its writing to a level which they were satisfied with. The validation of the interaction represents a significant step towards an innovative use for robotics which addresses a widespread and socially meaningful challenge in education

The impact of robot tutor nonverbal social behavior on child learning

Several studies have indicated that interacting with social robots in educational contexts may lead to a greater learning than interactions with computers or virtual agents. As such, an increasing amount of social human–robot interaction research is being conducted in the learning domain, particularly with children. However, it is unclear precisely what social behavior a robot should employ in such interactions. Inspiration can be taken from human–human studies; this often leads to an assumption that the more social behavior an agent utilizes, the better the learning outcome will be. We apply a nonverbal behavior metric to a series of studies in which children are taught how to identify prime numbers by a robot with various behavioral manipulations. We find a trend, which generally agrees with the pedagogy literature, but also that overt nonverbal behavior does not account for all learning differences. We discuss the impact of novelty, child expectations, and responses to social cues to further the understanding of the relationship between robot social behavior and learning. We suggest that the combination of nonverbal behavior and social cue congruency is necessary to facilitate learning

Can Children Catch Curiosity from a Social Robot?

Curiosity is key to learning, yet school children show wide variability in their eagerness to acquire information. Recent research suggests that other people have a strong influence on children's exploratory behavior. Would a curious robot elicit children's exploration and the desire to find out new things? In order to answer this question we designed a novel experimental paradigm in which a child plays an education tablet app with an autonomous social robot, which is portrayed as a younger peer. We manipulated the robot's behavior to be either curiosity-driven or not and measured the child's curiosity after the interaction. We show that some of the child's curiosity measures are significantly higher after interacting with a curious robot, compared to a non-curious one, while others do not. These results suggest that interacting with an autonomous social curious robot can selectively guide and promote children's curiosity.United States-Israel Educational Foundation (Fulbright Program)National Science Foundation (U.S.) (NSF Grant CCF-1138986

Social Robots as Embedded Reinforcers of Social Behavior in Children with Autism

In this study we examined the social behaviors of 4- to 12-year-old children with autism spectrum disorders (ASD; N = 24) during three tradic interactions with an adult confederate and an interaction partner, where the interaction partner varied randomly among (1) another adult human, (2) a touchscreen computer game, and (3) a social dinosaur robot. Children spoke more in general, and directed more speech to the adult confederate, when the interaction partner was a robot, as compared to a human or computer game interaction partner. Children spoke as much to the robot as to the adult interaction partner. This study provides the largest demonstration of social human-robot interaction in children with autism to date. Our findings suggest that social robots may be developed into useful tools for social skills and communication therapies, specifically by embedding social interaction into intrinsic reinforcers and motivators

2012 College Open House_10

Photos by Jim Svehla/Special to College of DuPagehttps://dc.cod.edu/marcom-studentlife-events/1173/thumbnail.jp