A conceptual framework for a symbiotic integration of generative AI in post-secondary technical and vocational education and training (TVET): Bridging pedagogy, technology, and ethics

Résumé

Generative Artificial Intelligence (GenAI) is poised to reshape Post-Secondary Technical and Vocational Education and Training (TVET), a sector critical for aligning formal education with industry demands. While the potential of GenAI is widely discussed, the literature lacks a holistic framework to guide its strategic and ethically sound integration. This paper addresses this gap by synthesizing existing research to develop a novel conceptual model for the symbiotic integration of GenAI in TVET.

This study employs an integrative literature review methodology. A purposive selection of recent, peer-reviewed literature (post-2020) was analyzed to synthesize key opportunities, such as hyper-personalized learning and immersive training, alongside significant systemic barriers, including infrastructural constraints, AI literacy gaps, and ethical risks. These insights were then structured into a multi-layered conceptual framework.

The review identifies three core domains of GenAI's impact: the evolution of pedagogy from standardization to personalization, the enhancement of learner engagement, and the reconceptualization of skills assessment. To navigate the complexities of implementation, the paper proposes the «Integrated Symbiotic Model». This model reframes GenAI integration as a collaborative «teacher-machine-student» ecosystem, structured across four interdependent layers: (1) foundational enablers (infrastructure, policy, AI literacy), (2) the core triad of actors (learner, educator, AI), (3) core pedagogical processes, and (4) the central objective of enhanced workforce readiness.

The primary contribution of this paper is the « Integrated Symbiotic Model », a novel framework designed to guide institutional leaders and educators in the strategic and ethically-grounded integration of GenAI. It moves beyond traditional technology adoption models to offer a pedagogically-focused, systemic roadmap for transforming TVET in the age of AI.

Classification JEL: O33, Q55, A20

Paper type: Theoretical Research