The FuturICT education accelerator

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year ‘man-on-the-moon’ project is proposed in which FuturICT’s unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a ‘wind tunnel’ for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT

The FuturICT education accelerator

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year ‘man-on-the-moon’ project is proposed in which FuturICT’s unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a ‘wind tunnel’ for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT

Resource-bounded modelling and analysis of human-level interactive proofs

Mathematics is the lingua franca of modern science, not least because of its conciseness and abstractive power. The ability to prove mathematical theorems is a key prerequisite in many fields of modern science, and the training of how to do proofs therefore plays a major part in the education of students in these subjects

The FuturICT education accelerator

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year 'man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a 'wind tunnel' for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT

The FuturICT education accelerator

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year 'man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a 'wind tunnel' for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT

Making social robots more attractive: the effects of voice pitch, humor and empathy

In this paper we explore how simple auditory/verbal features of the spoken language, such as voice characteristics (pitch) and language cues (empathy/humor expression) influence the quality of interaction with a social robot receptionist. For our experiment two robot characters were created: Olivia, the more extrovert, exuberant, and humorous robot with a higher voice pitch and Cynthia, the more introvert, calmer and more serious robot with a lower voice pitch. Our results showed that the voice pitch seemed to have a strong influence on the way users rated the overall interaction quality, as well as the robot's appeal and overall enjoyment. Further, the humor appeared to improve the users' perception of task enjoyment, robot personality and speaking style while the empathy showed effects on the way users evaluated the robot's receptive behavior and the interaction ease. With our study, we would like to stress in particular the importance of voice pitch in human robot interaction and to encourage further research on this topic

Cross-Cultural Perspectives on Emotion Expressive Humanoid Robotic Head: Recognition of Facial Expressions and Symbols

This article is closed access.Emotion display through facial expressions is an important channel of communication. However, between humans there are differences in the way a meaning to facial cues is assigned, depending on the background culture. This leads to a gap in recognition rates of expressions: this problem is present when displaying a robotic face too, as a robot’s facial expression recognition is often hampered by a cultural divide, and poor scores of recognition rate may lead to poor acceptance and interaction. It would be desirable if robots could switch their output facial configuration flexibly, adapting to different cultural backgrounds. To achieve this, we made a generation system that produces facial expressions and applied it to the 24 degrees of freedom head of the humanoid social robot KOBIAN-R, and thanks to the work of illustrators and cartoonists, the system can generate two versions of the same expression, in order to be easily recognisable by both Japanese and Western subjects. As a tool for making recognition easier, the display of Japanese comic symbols on the robotic face has also been introduced and evaluated. In this work, we conducted a cross-cultural study aimed at assessing this gap in recognition and finding solutions for it. The investigation was extended to Egyptian subjects too, as a sample of another different culture. Results confirmed the differences in recognition rates, the effectiveness of customising expressions, and the usefulness of symbols display, thereby suggesting that this approach might be valuable for robots that in the future will interact in a multi-cultural environment