将生成式人工智能引入教育中的自适应学习
Bringing Generative AI to Adaptive Learning in Education
AI总结：
本文探讨生成式人工智能与自适应学习结合的研究，分析其益处、挑战与潜力，论证该融合将推动下一代教育学习形式的发展。
摘要：
近期生成式人工智能技术的兴起，如大语言模型和扩散模型，推动了人工智能在科学、金融和教育等多个领域应用的发展。与此同时，自适应学习这一在教育领域已获得广泛关注的概念，已被证明在提升学生学习效率方面具有显著效果。在这篇立场论文中，我们旨在阐明这两种方法的交叉研究，即将生成式人工智能与自适应学习概念相结合。通过讨论该领域的益处、挑战和潜力，我们认为这种结合将为教育中下一代学习形式的发展做出重要贡献。
英文摘要：
The recent surge in generative AI technologies, such as large language models and diffusion models, has boosted the development of AI applications in various domains, including science, finance, and education. Concurrently, adaptive learning, a concept that has gained substantial interest in the educational sphere, has proven its efficacy in enhancing students' learning efficiency. In this position paper, we aim to shed light on the intersectional studies of these two methods, which combine generative AI with adaptive learning concepts. By presenting discussions about the benefits, challenges, and potentials in this field, we argue that this union will contribute significantly to the development of the next-stage learning format in education.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
