  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.
