Humanoid robot as learning media has the potential of approaching not only cognitive aspect but also affective aspect of learning, which is mainly due to its social presence. The social presence originates from its anthropomorphized and embodied media. In addition to the social presence, nonverbal behavior to be conducted by humanoid robot could also bring about learners’ affectivity/emotion contributing to cognitive benefits. Related work on learning with social robot has been referring to human communication behavior and its model to explore the effects and possibility of robot communicating with learners. This paper describes the current states of learning with social robot. This paper also introduces a new approach to designing a model for robot behavior to develop social robot as learning media, and demonstrates a robot lecture system for promoting learners’ engagement in lecture. Let me finally discuss future issues including model design and adaptation for robot–learner interaction.

Many household devices have become IoT. IoT is a mechanism in which devices such as sensors, actuators, home appliances, and automobiles are connected to a network and exchange information with each other. The use of IoT in schools has the potential to realize new learning methods such as independent learning and collaborative learning as well as energy-saving and efficiency. By using IoT, it will be possible to learn to develop logical thinking ability and imagination ability while interacting with the detailed environment in the real world. In this paper, we introduce IoT devices that are available and learning using them.

In recent years, learning analytics, educational data mining, and institutional research have been developed as research areas on data utilization in education and learning. In particular, knowledge of many studies on utilization of predictive models by machine learning is accumulating. In this paper, the various fields of data utilization in education and learning are first reviewed, and then the trends in research on the use of predictive models in these fields and our research so far are introduced. Finally, future issues in this field are summarized.

We have developed a learning environment for programming education using LEGO. In this research, we have realized a system that can easily integrate devices created by individual learning in cooperative learning by making the LEGO EV3 into IoT device. In this learning environment, learners not only can integrate real world equipment, but also can easily control the other equipment depending on the state of the equipment. Learners were able to seamlessly participate in cooperative learning after concentrating on individual learning.

In previous work on recognizing situations of lectures from their videos for reviewing those lectures to improve them, the behavior of looking ahead has been focused as the situation to be considered for the students, whereas various behaviors including pointing at slides, writing on the whiteboard, speaking to the students and so on have been considered as the situations for the lecturer. However, various behaviors of the students such as taking notes, dozing off, and so on as well as looking ahead could also be useful to estimate their understanding of the lecture. Since it is unknown what kinds of behaviors are actually observed in the students in the class beforehand, and the postures actually taken for those behaviors differ with each student, it is proposed in this article to obtain the situations actually observed in the students during the class by clustering their postures obtained from the lecture videos.

Citizen-centered design has been essential for global data utilization smart cities. We developed a data utilization skill development program, which contains a prototyping support environment for data utilization services. We implemented the program in a seminar course for general public. In this paper, we describe a usefulness of the program for creating ideas to solve regional problems using data based on results of the practice.