AI-Powered Learning: Increasing User Retention and Productivity Through Personalised Learning Paths

人工智能领域最近的创新已经在所有行业，特别是在教育领域掀起了颠覆性的浪潮。世界各地的学校已经禁止使用ChatGPT，担心它对学习的影响，而教育科技初创公司则抓住了降低教育障碍的机会。离线和在线学习之间的鸿沟越来越大，学校和高等教育被迫提供混合学习方法。知识已经成为一种商品。为了保持相关性和经济竞争力，学习机构需要调整和重新关注其教学方法，而不是知识本身，而是其交付机制，以便学生在学习中茁壮成长，遇到困难时得到支持，并被吸引继续学习。该项目由音乐技术在线学习平台Music Hackspace领导，和伦敦艺术大学创意计算研究所。它专注于研究个性化学习之旅的可行性，使用Music Hackspace在2020年至2023年期间创建的300多个点播课程的现有资源库。该项目将分析Music Hackspace课程的成绩单，帮助学生发现新内容并决定学习什么，并提供基于学生需求和背景的定制建议的对话工具。两个团队在2021年合作获得IUK资助，以构建一个机器学习引擎，按复杂性对课程进行排名。该项目是当时开始的成功研究的延续，但没有使用大型语言模型。这些团队有一个现有的代码库和原型，一个明确的IP策略，并习惯于一起工作。这个项目利用了三个关键组件：（1）Rebecca Fiebrink教授团队的世界级机器学习和音乐技术专业知识，（2）学者和专业人士的在线教学和面对面教学经验，（3）一个蓬勃发展的创业公司，理想地整合这项研究的结果，以获得牵引力和市场份额。Statista估计，全球电子学习市场的年复合增长率为9.84%（2023年：1330亿英镑，2027年：1910亿英镑），而全球音乐电子学习领域的增长速度是其两倍（2023年：1.74亿英镑，2027年：3.41亿英镑/复合年增长率：18.40%，研究与市场），这突显出迫切需要加强英国在这个快速增长的行业中的地位。机器学习是在这个领域实现差异化创新的关键。该项目的成功完成预计将使MHS的收入比目前的预测增加62%，这突出了人工智能在教育领域的变革潜力。

The 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.