Artificial Intelligence and the Didactic Transposition of Knowledge: Implications for Curriculum Development and Knowledge Gatekeeping
DOI:
https://doi.org/10.57125/FED.2025.06.25.03Keywords:
Artificial Intelligence, didactic transposition, Curriculum development, ‘ReKnow-AI’ modelAbstract
This article explores how artificial intelligence (AI) is reshaping the transformation of scientific knowledge into school knowledge, a process traditionally conceptualized through the lens of didactic transposition theory. Drawing from curriculum theory, philosophy and sociology of education, and educational technology, the study examines two key dimensions: the use of AI in curriculum development and textbook authorship, and the role of algorithmic systems in selecting and structuring pedagogically relevant content. A conceptual model, “ReKnow-AI”, is proposed to illustrate how AI can be integrated into all stages of knowledge mediation, from scientific production to classroom practice. The study employs a theoretical and conceptual methodology, grounded in interdisciplinary content analysis. It proceeds through a systematic literature review and comparative synthesis of over 60 international sources published between 2020 and 2025, covering educational research, digital pedagogy, and AI-driven instructional design. No empirical data or statistical tools were employed; instead, conceptual modelling was used to identify epistemic shifts in curriculum-making under AI mediation. Findings highlight pedagogical opportunities such as content personalization, dynamic updating, and real-time instructional support. However, they also underline risks associated with algorithmic bias, lack of transparency, and diminished teaching agency. The proposed “ReKnow-AI” model identifies the critical junctures where AI systems influence educational content and advocates for ethical, human-centered oversight. This research contributes a novel perspective by framing AI not merely as a technological aid but as an epistemic actor in curriculum construction. Its practical significance lies in informing curriculum designers, policymakers, and teacher educators about the structural and normative implications of AI-based content mediation in contemporary education.
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