Abstract: This paper introduces the Metacognitive Creative Destruction (MCD) Model to explain how educational disruptive inno-vation can emerge through cognitive deconstruction and reconstruction processes in Artificial Intelligence (AI) enhanced environments. While prior research explores metacognition, unlearning, and educational change separately, an integrat-ed model explaining how individuals intentionally dismantle outdated knowledge structures to foster adaptive and in-novative learning has not emerged, yet. Grounded on Schumpeter’s theory of “Creative Destruction”, the MCD model conceptualizes “Destruction” at the cognitive level, where AI acts as a metacognitive spark for reflective disruption and epistemic revision. The model, which was developed to monitor the educational transition towards disruptive innova-tion, includes thirteen (13) empirically tested variables grouped into core adaptive capacities, contextual enablers / inhib-itors, and learning outcomes. To validate the concept, quantitative primary research took place and data from 1,498 cur-rent and alumni students-educators of the “Administration and Management of Education Units” postgraduate program of the International Hellenic University in Greece were analyzed using structural equation modeling (SEM). Results confirmed the model’s robustness and predictive validity towards disruptive educational innovation. The findings sug-gest that fostering in a recursive learning cycle, metacognitive flexibility, unlearning propensity, epistemic humility, the incorporation of AI as cognitive and reflective partner and psychological readiness for revision may significantly en-hance knowledge reconstruction and disruptive innovation in education systems. In a sentence, the study aims to share with academia, both a validated measurement model and a theoretical lens for understanding transformational learning towards disruptive innovation, in the AI era.

Submitted: January 2026, Revision Submitted: March 2026, Accepted: April 2026