The digital transformation of our society has deeply impacted the way we interact, communicate, and learn. This new digital era raises exceptional challenges for teaching and learning, particularly in adapting to individual learning paces, providing adequate progress traceability, and ensuring inclusive solutions for diverse learners. This paper introduces an Autonomic Cyber-Physical System for Education (A-CPS-E) that addresses these challenges through a framework combining teaching and learning design patterns with autonomous system capabilities. The A-CPS-E implements the autonomic computing paradigm to adapt learning experiences across four instructional interaction modes and generates Augmented Interactive Learning Objects (AILO) using AI support to enhance the teaching and learning process. We deployed the system within the Erasmus+ Connect Unita project, engaging 484 learners and 100 teachers across 12 universities in Europe. Resulting in the creation of 14 international training programs, including 65 learning paths and 400 learning objects, with 91.3% remote engagement. Preliminary results have allowed us to evaluate the benefits of the A-CPS-E in providing adaptive, traceable, and inclusive educational experiences that transcend traditional boundaries in higher education.