This research analyzes, models and develops a novel Digital Learning Environment (DLE) fortified by the innovative Private Learning Intelligence (PLI) framework. The proposed PLI framework leverages federated machine learning (FL) techniques to autonomously construct and continuously refine personalized learning models for individual learners, ensuring robust privacy protection. Our approach is pivotal in advancing DLE capabilities, empowering learners to actively participate in personalized real-time learning experiences. The integration of PLI within a DLE also streamlines instructional design and development demands for personalized teaching/learning. We seek ways to establish a foundation for the seamless integration of FL into learning systems, offering a transformative approach to personalized learning in digital environments. Our implementation details and code are made public.

翻译：本研究分析、建模并开发了一种由创新性私有学习智能（PLI）框架赋能的新型数字学习环境（DLE）。所提出的PLI框架利用联邦机器学习（FL）技术自主构建并持续优化面向个体学习者的个性化学习模型，确保强大的隐私保护能力。该方法在提升DLE功能方面具有关键意义，能够赋能学习者积极参与个性化实时学习体验。将PLI集成至DLE还可简化个性化教学/学习中的教学设计与开发需求。我们致力于为FL与学习系统的无缝集成奠定基础，为数字环境中的个性化学习提供变革性方案。本研究的实现细节与相关代码已公开。