This paper presents the results of an experimental study in which users teleoperating a mobile robot evaluated three controllers: a keyboard, a game controller, and a touchpad interface. It is motivated by the need to engage a broader, non-expert user audience in teleoperation as robots become more prevalent in everyday applications. Analysis focuses on how specific control elements and the user's comfort with a device improve the operator's sense of immersion in the task and how this alters performance. Our results show that perceived controllability of the controller, users' level of technological anxiety, and the physical nature of feedback from the controller had an effect on user feelings of immersion and presence. Our findings have implications for the development of controllers that can be used for teleoperating robots by a broad user audience.

This paper contributes to the study of interaction between groups of people and groups of robots by examining the effect of group size on people's attitudes and behaviors toward robots as interaction partners. Our work is motivated by psychological research on human intergroup dynamics, particularly the interindividual-intergroup discontinuity effect, which suggest that interactions among groups are more competitive than interactions among individuals. To test the discontinuity effect in the context of human-robot interaction, we conducted a between-subjects experiment with four conditions, derived by differentiating the ratio of humans to robots in the interaction (one or two humans interacting with one or two robots). Participants played a game with robots in which they were given a chance to exhibit competitive and cooperative behaviors, which we tracked. We also measured changes in participants' attitudes toward robots following gameplay. Our results show that people playing in groups behave more competitively towards the robots than individual human players. However, participants' attitudes toward robots did not change after the short-term interaction.

In this paper, we describe the results of a comparative analysis of user-created designs for future domestic robots made by participants in Korea and the US. We identify their culturally variable expectations and preferences. We use a generative design methodology, which includes users visualizing their designs followed by semi-structured interviews. We describe our results in four areas of design: the look and feel of the robot, interaction mode, social role, and desired task. We identify variable cultural models relating to robotic technology and the cultural meaning of the domestic context as central factors. Finally, we discuss the design implications of our findings to culturally situated robot design.

Abstract The use of Social Network Analysis (SNA) for online learning communities’ analysis is common and usually performed after the ending of semester. Yet, even if such analysis is very useful, it is costly, and cannot be performed many times during the semester. In this paper, we present a model of automated SNA based inference, for a large- scale community, taking into account specific environment of developing higher education system. The model is designed so to send automated reminders to all users, according their activity in the period of two weeks. One additional analysis after the mid-term exams checks if activity matches performance. It has crucial role in directing both students and educators towards the common goal: success at the final exams. The presented model enables inference on user attributes, which are stored in student model ontology. As such, the model is a step in the development of semantic and adaptive learning environment.