Using Adaptive Inbodied Motor e-learning Interactions to improve cognitive performance in language acquisition

To develop novel interactive tools and techniques to explore learning in motion.
Research shows that movement enhances learning both inside and outside the classroom.
Research also clearly shows across demographics that long periods of both sitting and looking at screens induces poor cognitive performance as well as associated physical risks from illness to elevated stress.

e-Learning - becoming even more of a focus in COVID19 lockdown - embraces the worst of knowledge work ICT: sedentary practices with fixed screen.

The work in this phd will explore how we can develop new tools to enhance e-Learning by combining physiology of learning, theories of learning (eg motor learning) in order to support learning that is out of the chair, off the desktop and mobile, in the environment; leveraging AR and AI in particular.

The target case will be supporting language acquisition - language and movement leverage complementary areas of the brain; language acquisition is of particular concern for students coming to the UK, for workers increasing opportunities for collaboration, and for creativity.

Contributions will be to human systems interaction; human centred AI; e-Learning; mobile computing.