This study reports the advantages of using a child-operated telepresence robot system for the purpose of remote education. Video conferencing is already common in educational settings, where a foreign language is taught by a native teacher from a remote location; however, there is a serious issue in that children tend to have difficulties or freeze when facing teachers who speak a different language over a monitor. We hypothesize that a child-operated telepresence robot that offers physical participation and operability will help to address this issue. To investigate this hypothesis, we conduct a field experiment with 52 participants (4-8 years old) in classroom environments, and the use of a telepresence robot system is compared with a baseline Skype condition. The results show the advantages of the telepresence robot system for both children and teachers.

Detection of emerging topics is now receiving renewed interest motivated by the rapid growth of social networks. Conventional-term-frequency-based approaches may not be appropriate in this context, because the information exchanged in social-network posts include not only text but also images, URLs, and videos. We focus on emergence of topics signaled by social aspects of theses networks. Specifically, we focus on mentions of users--links between users that are generated dynamically (intentionally or unintentionally) through replies, mentions, and retweets. We propose a probability model of the mentioning behavior of a social network user, and propose to detect the emergence of a new topic from the anomalies measured through the model. Aggregating anomaly scores from hundreds of users, we show that we can detect emerging topics only based on the reply/mention relationships in social-network posts. We demonstrate our technique in several real data sets we gathered from Twitter. The experiments show that the proposed mention-anomaly-based approaches can detect new topics at least as early as text-anomaly-based approaches, and in some cases much earlier when the topic is poorly identified by the textual contents in posts.

This paper reports the research outcome of a JST PRESTO project “Linking children across the world through telerobotics (2009-2013).” The project explored the use of child-operated telepresence robot systems for the purpose of facilitating international communication between distant classrooms. In particular, it was revealed that young children who could not communicate well with speakers of different languages over conventional video conference services could establish and maintain communication using the telepresence robot system developed by this project. Together with a control experiment to clarify its effectiveness, an international field trial that connected remote classrooms between Australia and Japan was conducted.

We consider the application of telepresence robots for supporting childhood education. One challenge here is to develop a teleoperational robot system that can be manipulated by children themselves. There are two requirements for realizing such a system. First, the system has to be sufficiently intuitive so that child users can control it without the need for detailed instructions. Second, the control of the system should have some amount of enjoyment so that child users do not get bored. To satisfy these requirements, we introduce a tricycle-style teleoperational interface that remotely controls a robot. We also report field tests that are currently being conducted at English learning schools for children in Japan.

A tricycle-style teleoperational interface for children to remotely control a robot was developed. There were two crucial requirements in its design: (1) the interface had to be intuitively controllable so that children could use it without requiring detailed instructions and (2) the control of the teleoperational system needed to be fun so that children did not get bored. In this paper, we report an experiment in which 20 children (4-8 years old) performed a range of tasks by remotely controlling a robot using two types of teleoperational interfaces: the tricycle-style interface and a standard video game controller. The results show that the children could perform the tasks better with the tricycle-style interface.

The paper describes our project whose final goal is to link remote classrooms by telerobotics. The first target is to offer children in Japan an opportunity to remote-control a robot placed in an US classroom, and participate in the classroom activities. By conducting field trials at nursery schools and language schools for children, we aim to identify and solve critical problems which might prevent this potentially popular technology from becoming a reality. Here, we will report the development of a remote-hand device which seems to be the most required element for the proposed system.

Detection of emerging topics are now receiving renewed interest motivated by the rapid growth of social networks. Conventional term-frequency-based approaches may not be appropriate in this context, because the information exchanged are not only texts but also images, URLs, and videos. We focus on the social aspects of theses networks. That is, the links between users that are generated dynamically intentionally or unintentionally through replies, mentions, and retweets. We propose a probability model of the mentioning behaviour of a social network user, and propose to detect the emergence of a new topic from the anomaly measured through the model. We combine the proposed mention anomaly score with a recently proposed change-point detection technique based on the Sequentially Discounting Normalized Maximum Likelihood (SDNML), or with Kleinberg's burst model. Aggregating anomaly scores from hundreds of users, we show that we can detect emerging topics only based on the reply/mention relationships in social network posts. We demonstrate our technique in a number of real data sets we gathered from Twitter. The experiments show that the proposed mention-anomaly-based approaches can detect new topics at least as early as the conventional term-frequency-based approach, and sometimes much earlier when the keyword is ill-defined.