The project will bring together scientific experts and renowned dance schools to identify the best strategies to support remote dance teaching, learning and artistry.
For the study, the researchers will evaluate the best format for delivering feedback to dance students being taught remotely, and investigate the potential for AI to train additional skills at home.
Taught by experts
Students participating in the project will be taught remotely by leading choreographer and dance teacher, Erico Montes, with support from other dance professionals including ballet choreographer and Lecturer in Dance at The London Contemporary Dance School Raymond Chai, and professional ballet and Floor Barre teacher and Ballet Mistress to Rambert2, Ms Nina Thilas-Mohs.
The researchers will work with well-known dance schools including the English National Ballet School and the Trinity Laban Conservatoire of Music and Dance. Other vocational schools are also expected to participate.
Dr Elisabetta Versace, Lecturer in Psychology at Queen Mary University of London and project lead, said: “Whilst many teaching practices have validated methods to transition to remote learning, the training of motor and artistic skills, such as dance, can be particularly challenging. We hope this study will provide us with improved knowledge on teaching methods that could support and enhance remote learning in the arts and sports, as well as mitigate the effects of social distancing on a wide range of physical, psychological, artistic, and cognitive outcomes.”
Using AI for immediate feedback
Through this project, the multidisciplinary research team will develop AI tools that will help dancers receive feedback on their movements in the absence of in-person teaching. This could provide teachers with an opportunity to train skills, such as refined movements, synchrony and self-evaluation, which are normally difficult to teach in remote settings.
Professor Andrea Cavallaro, Professor of Multimedia Signal Processing at Queen Mary University of London and Director of the Centre for Intelligent Sensing, said: “We will develop data-driven algorithms to compare the movements of a student with those of our choreographer, in order to understand what they are doing differently and how they can correct their performance. For example, we will evaluate whether a student moves early or late, and how they articulate limbs and other parts of the body. This will enable us to provide individual, immediate feedback.”
Dr Versace added: “Whilst there are many immediate downsides to this for those involved in the sector, in the longer term there’s a possibility that the shift to remote interactions could present new opportunities to interact and enhance creative projects and learn artistic skills. Often we think of the arts and technology being in competition, but through this project we hope to show how technology, and specifically AI, could actually be used to enhance the arts.”
New tools for training and physiotherapy
The project will also take advantage of the expertise available at Queen Mary’s Centre for Sports and Exercise Medicine to develop new tools and techniques for the remote learning other motor skills in a wider range of settings, including physiotherapy and sports. Dancers will be assessed for physical and physiological traits under the supervision of Dr Manuela Angioi and a feasibility study with injured dancers will also take place at the NHS Dance Medicine clinic at Mile End Hospital, led by Professor Dylan Morrissey, Clinical Professor and Consultant Physiotherapist at the Centre.
Dr Manuela Angioi, Senior Lecturer in Sports and Exercise Medicine at Queen Mary University of London and fellow of the International Association for Dance Medicine & Science (IADMS), said: “We have previously investigated the physical and physiological requirements of dance related activities and we offer research support to a number of Institutions by analysing data in relation to annual physical screening, including the English National Ballet School and the Royal Ballet School. This project will allow us to better understand how selected physical fitness components and aesthetic competence respond to online delivery”.
“The collaboration between psychology, sports science and dance medicine will be essential to adapt these AI tools for training and physiotherapy purposes, where patients require feedback from specialists on how appropriate their movements are for rehabilitation and training.”
The research project is supported by funding from the Economic and Social Research Council (ESRC), part of UK Research and Innovation, and will run for a period of 12 months.