The role of social networks in students’ learning experiences

The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined

Using a simulated student to repair difficulties in collaborative learning

We describe the use of a simulated student in a synchronous but distributed collaborative learning environment in the domain of programming. The role of the simulated student is to detect and repair difficulties in collaborative learning amongst the human students, for example when a human student is too passive or when the students start chatting about off-topic conversations. The simulated student intervenes by posting messages in the shared "chat" window, just like the human students and was believed to be another human student by them. The paper describes the rules by which the simulated student operates and briefly outlines an evaluation of the system with university first year programming students. The system proved to be successful both in detecting a range of difficulties and in intervening effectively

Towards the Safety of Human-in-the-Loop Robotics: Challenges and Opportunities for Safety Assurance of Robotic Co-Workers

The success of the human-robot co-worker team in a flexible manufacturing environment where robots learn from demonstration heavily relies on the correct and safe operation of the robot. How this can be achieved is a challenge that requires addressing both technical as well as human-centric research questions. In this paper we discuss the state of the art in safety assurance, existing as well as emerging standards in this area, and the need for new approaches to safety assurance in the context of learning machines. We then focus on robotic learning from demonstration, the challenges these techniques pose to safety assurance and indicate opportunities to integrate safety considerations into algorithms "by design". Finally, from a human-centric perspective, we stipulate that, to achieve high levels of safety and ultimately trust, the robotic co-worker must meet the innate expectations of the humans it works with. It is our aim to stimulate a discussion focused on the safety aspects of human-in-the-loop robotics, and to foster multidisciplinary collaboration to address the research challenges identified