10079009AI-Powered Learning: Increasing User Retention and Productivity Through Personalised Learning PathsClosedCollaborative R&DInnovate UKThe recent innovations in Artificial Intelligence have sent disrupting waves across all industries, and across the Education sector in particular. Schools around the world have banned the use of ChatGPT, fearing its impact on learning, while edtech startups embraced the opportunity to lower barriers to education. The divide between offline and online learning grows stronger, and schools and higher education are forced to offer hybrid approaches to learning. Knowledge has become a commodity. To remain relevant and economically competitive, learning institutions need to adapt, and refocus their pedagogical approach not on the knowledge itself, but on its delivery mechanisms, such that students will thrive in their learning, be supported when encountering difficulties and be enticed to continuously learn. This project is led by Music Hackspace, an online learning platform for music technologies, and the Creative Computing Institute of University of the Arts London. It focuses on studying the feasibility of personalised learning journeys, using an existing repository of over 300 on-demand courses created by Music Hackspace between 2020 and 2023\. The project will analyse the transcripts of Music Hackspace courses to help students discover new content and decide what to study, with a conversational tool that offers bespoke advice based on student needs and contexts. Both teams have collaborated on a IUK grant in 2021, to build a Machine Learning powered engine to rank courses by complexity. This project is a continuation of the successful research started then, but which didn't use large language models. The teams have an existing codebase and prototype, a clear IP strategy, and are used to working together. This project leverages three key components: (1) the world-class Machine Learning and music technology expertise of Prof Rebecca Fiebrink's team, (2) the experience of teaching online and in-person of academics and professionals, (3) a thriving startup ideally positioned to integrate the results of this research to gain traction and market share. Statista estimates the global e-learning market to grow CAGR 9.84%(2023:£133B,2027:£191B), while the global music e-learning segment grows twice as fast (2023: £174M,2027:£341M/CAGR:18.40%, Research&Markets), highlighting an urgent need to bolster the UK position in this rapidly growing sector. Machine Learning is key to differentiating innovation in this space. Successful completion of this project is projected to increase MHS's revenue by 62% over its current forecast, underscoring the transformative potential of AI in education.