IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05243404.html
   My bibliography  Save this paper

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
[Un Cadre Conceptuel Pour L'Intégration Symbiotique De L'Ia Générative Dans L'Enseignement Et La Formation Professionnels Et Techniques (Efpt) Postsecondaires : Allier Pédagogie, Technologie Et Éthique]

Author

Listed:
  • Mounaim El Hayani

    (Kénitra - Ecole nationale de commerce et gestion Ibn Tofail)

  • Fatiha Benamar

    (Kénitra - Ecole nationale de commerce et gestion Ibn Tofail)

Abstract

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. Keywords: Integrated Symbiotic Model, Generative AI, TVET, Pedagogical Transformation, Learner Engagement, Skills Assessment.

Suggested Citation

  • Mounaim El Hayani & Fatiha Benamar, 2025. "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 [Un Cadre Con," Post-Print hal-05243404, HAL.
  • Handle: RePEc:hal:journl:hal-05243404
    Note: View the original document on HAL open archive server: https://hal.science/hal-05243404v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-05243404v1/document
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-05243404. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.