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

最近人工智能的创新给所有行业带来了颠覆性的浪潮，尤其是在教育领域。世界各地的学校都禁止使用ChatGPT，担心它会影响学习，而教育科技初创公司则抓住了这个降低教育门槛的机会。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的学习方法。知识已经成为一种商品。为了保持相关性和经济竞争力，学习机构需要适应并重新调整其教学方法，而不是关注知识本身，而是关注其提供机制，这样学生才能在学习中茁壮成长，在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和伦敦艺术大学创意计算研究所牵头。它的重点是研究个性化学习之旅的可行性，使用由Music Hackspace在2020年至2023年期间创建的300多个按需课程的现有存储库。该项目将分析音乐黑客空间课程的成绩单，帮助学生发现新的内容，并决定学习什么，通过一个会话工具，根据学生的需求和背景提供定制的建议。这两个团队在2021年合作获得了IUK的资助，以建立一个机器学习驱动的引擎，根据复杂性对课程进行排名。这个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。团队拥有现有的代码库和原型，明确的IP策略，并且习惯于一起工作。该项目利用了三个关键组成部分：(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和面对面教学经验；(3)一家蓬勃发展的初创公司，理想定位于整合这项研究的结果，以获得吸引力和市场份额。Statista估计全球电子学习市场将以9.84%的复合年增长率增长（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%,Research&Markets），突出了迫切需要加强英国在这一快速增长领域的地位。机器学习是这个领域差异化创新的关键。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%，凸显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.