Pedagogical architectures of distributed cognition: rethinking teacher-researcher formation and generative artificial intelligence

Abstract

ABSTRACT: The rapid incorporation of generative artificial intelligence into scientific research has triggered a broad institutional response centered on governance, integrity, and technological literacy. This article argues that such responses, while necessary, leave relatively unexplored a prior question: how the contemporary reorganization of scientific activity changes the conditions under which researchers learn to produce knowledge. Drawing on research-formation literature, the tradition of pedagogical architectures, and distributed cognition theory, it proposes the category of Pedagogical Architetures of Distributed Cognition (PADC) to describe how cognitive operations, subjects, artifacts, and forms of legitimation are distributed across scientific formation in contexts of artificial intelligence. The article develops the category's operational definition, proposes a four-dimension analytical matrix and a typology of three formative arrangements, and discusses implications for supervision, curriculum, and assessment in graduate programs. The proposal is presented as theoretical-conceptual elaboration and a research program, whose empirical validation remains an agenda for future research. The process of preparing this article involved the use of generative Artificial Intelligence tools, detailed in a specific section at the end of the manuscript.