Generative Artifcial Intelligence and Extended Cognition

This paper philosophically examines the impact of generative artifcial intelligence on learning processes from the perspective of extended cognition. The central problem addressed is how these technologies can transform students into passive or active learners, infuencing the development of cognitiv...

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Autores:
Rivera Novoa, Ángel Giovanni
Duarte Arias, Daniel Augusto
Tipo de recurso:
Article of investigation
Fecha de publicación:
2025
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/46452
Acceso en línea:
https://hdl.handle.net/10495/46452
Palabra clave:
Inteligencia artificial
Artificial intelligence
Tecnología educacional
Educational technology
Aprendizaje activo
Activity learning
Innovación educacional
Educational innovations
Cognición
Cognition
http://vocabularies.unesco.org/thesaurus/concept3052
http://vocabularies.unesco.org/thesaurus/concept97
http://vocabularies.unesco.org/thesaurus/concept1304
http://vocabularies.unesco.org/thesaurus/concept7281
http://vocabularies.unesco.org/thesaurus/concept387
ODS 4: Educación de calidad. Garantizar una educación inclusiva y equitativa de calidad y promover oportunidades de aprendizaje permanente para todos
Rights
openAccess
License
http://creativecommons.org/licenses/by/4.0/
Description
Summary:This paper philosophically examines the impact of generative artifcial intelligence on learning processes from the perspective of extended cognition. The central problem addressed is how these technologies can transform students into passive or active learners, infuencing the development of cognitive skills. It will be argued that generative artifcial intelligence presents risks of diminishing cognitive activity among students, as it is likely to substitute—rather than complement—the cognitive subject. It will also be argued that there are ways to leverage generative artifcial intelligence so that learners are not passive but rather active cognitive subjects. Three cases will be presented, with empirical support, to show how this leveraging is possible: the production of feedback, assistive technologies, and gamifcation. In these cases, generative artifcial intelligence is a complementary cognitive artifact rather than a substitutive one. To achieve this goal, the paper presents the framework of the extended mind thesis as a conducive scenario for analyzing the relationship between generative artifcial intelligence and learning contexts, and it analyzes specifc cases of science education. An analysis of the types of cognitive artifacts will also be conducted to examine how generative artifcial intelligence intervenes in learning in both substitute and complementary ways.