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Cybernetic Insights on GenAI and Learning in Higher Education

Journal
2026 IEEE Engineering Education World Conference (EDUNINE)
Publisher
IEEE
Date Issued
2026
Author(s)
Salinas-Navarro, David Ernesto  
Facultad de Ingeniería - CampCM  
Vilalta-Perdomo, Eliseo
Type
text::conference output::conference proceedings
DOI
10.1109/EDUNINE62390.2026.11546841
URL
https://scripta.up.edu.mx/handle/20.500.12552/13109
Abstract
The rapid diffusion of Generative Artificial Intelligence (GenAI) is reshaping learning conditions, not by introducing new activities but by reorganising existing feedback structures among students, teachers, and learning environments. This study adopts a cybernetic perspective to explore how Gen AI influences the recursive processes of enquiry, collaboration, and reflection. Drawing on the concepts of feedback, adaptation, and regulation, this paper frames GenAI as an active participant in learning systems, redistributing agency, and reshaping the rhythm of interaction. A methodological guide is proposed for constructing case studies across disciplines, combining documentary artefacts and participant accounts to map the cybernetic dynamics in practice. A case study of a Quality Management module illustrates how GenAI reconfigures individual reflection, group collaboration, and assessment practices. This study contributes to cybernetic learning theory by showing how GenAI affects agency and feedback structures, and by providing a framework for designing ethical GenAI learning environments. This study acknowledges the limitations that future studies must address to examine student learning outcomes. The paper concludes by highlighting the research question: How does Gen AI reshape learning as a recursive cybernetic process? Scholars are invited to explore this in their own contexts in future studies. © The authors © IEEE.
Subjects

Learning (artificial ...

Artificial intelligen...

Cybernetics

Feedback

Printing

Reflection

Design methodology

Modeling

Collaboration

Context

License
Acceso Restringido
URL License
https://creativecommons.org/licenses/by-nc-sa/4.0/
How to cite
Salinas-Navarro, D. E., & Vilalta-Perdomo, E. (2026). Cybernetic Insights on GenAI and Learning in Higher Education. In 2026 IEEE Engineering Education World Conference (EDUNINE) (pp. 1–6). IEEE. 2026 IEEE Engineering Education World Conference (EDUNINE). https://doi.org/10.1109/edunine62390.2026.11546841
Table of contents
Document Sections -- I. Introduction -- II. Theoretical Background-- III. A Methodology for Cybernetic Exploration -- IV. A Summarised Case on Industrial Engineering -- V. Conclusions.

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