Purpose Education in the age of AI faces an epistemic paradox: It can increasingly observe learning through data and analytics, yet it still struggles to understand learning as a process of meaning. While modern systems exhibit a degree of technical reflexivity, their feedback remains largely procedural and detached from interpretation. Design/Approach/Methods This article proposes the Parallel Distributed Processing (PDP)–Innovation, Creativity, and Entrepreneurship Education (ICEE) Learning System as a bridge from educational philosophy to design practice and computational modeling—a distributed architecture that enables education to learn about its own learning. Integrating the Human-in-the-Loop (HITL) principle with the philosophy of ICEE, the model redefines education as a reflexive and self-evolving system capable of transforming technical feedback into epistemic understanding. Findings The study develops this integration across five levels: (a) diagnosing the limits of current educational reflexivity, (b) articulating human–machine co-learning as systemic reflection, (c) operationalizing reflexivity through the Task Chain and Crystal System, (d) formalizing these dynamics within a PDP architecture, and (e) situating them within Panarchy theory to explain how education evolves as a complex adaptive system. Originality/Value By translating educational philosophy into computational and design logic, the PDP–ICEE Learning System offers a new epistemic form of education—one capable of learning from learning, integrating reflection, design, and evolution within a single self-observing framework.
Ruojun Zhong (仲若君) (Sun,) studied this question.