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dc.contributor.authorGriffiths, Dai
dc.contributor.authorFrías-Martínez, Enrique
dc.contributor.authorTlili, Ahmed
dc.contributor.authorBurgos, Daniel
dc.date2024-03
dc.date.accessioned2024-03-12T13:07:12Z
dc.date.available2024-03-12T13:07:12Z
dc.identifier.citationGriffiths, D., Frías-Martínez, E., Tlili, A. & Burgos, D. (2024). "A Cybernetic Perspective on Generative AI in Education: From Transmission to Coordination", International Journal of Interactive Multimedia and Artificial Intelligence, vol. 8, issue Special issue on Generative Artificial Intelligence in Education, no. 5, pp. 15-24. https://doi.org/10.9781/ijimai.2024.02.008es_ES
dc.identifier.urihttps://reunir.unir.net/handle/123456789/16207
dc.description.abstractThe recent sudden increase in the capabilities of Large Language Models (LLMs), and generative AI in general, has astonished education professionals and learners. In formulating a response to these developments, educational institutions are constrained by a lack of clarity concerning human-machine communication and its relationship to models of education. Ideas and models from the cybernetic tradition can help to fill this gap. Two paradigms are distinguished: (1) the transmission paradigm (combining the model of learning implied by the instruments and processes of formal education and the conduit model of communication), and (2) the coordination paradigm (combining the constructivist model of learning and the coordination model of communication). It is proposed that these paradigms have long coexisted in educational practice in a modus vivendi, which is disrupted by LLMs. If an LLM can pass an examination, then from within the transmission paradigm this can only understood as demonstrating that the LLM has indeed learned and understood the material being assessed. At the same time, we know that LLMs do not in fact have the capacity to learn and understand, but rather generate a simulacrum of intelligence. It is argued that this paradox prevents educational institutions from formulating a coherent response to generative AI systems. However, within the coordination paradigm the interactions of LLMs and education institutions can be more easily understood and can be situated in a conversational model of learning. These distinctions can help institutions, educational leaders, and teachers, to frame the complex and nuanced questions raised by GenAI, and to chart a course towards its effective use in education. More specifically, they indicate that to benefit fully from the capabilities of generative AI education institutions need to recognize the validity of the coordination paradigm and adapt their processes and instruments accordingly.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 8, nº 5
dc.rightsopenAccesses_ES
dc.subjecteducationes_ES
dc.subjectcyberneticses_ES
dc.subjectgenerative AIes_ES
dc.subjecthuman-machine communicationes_ES
dc.subjectlarge language models (LLM)es_ES
dc.subjectmachine learninges_ES
dc.subjectIJIMAIes_ES
dc.titleA Cybernetic Perspective on Generative AI in Education: From Transmission to Coordinationes_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2024.02.008


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