02683nas a2200265   4500000000100000000000100001008004100002260001200043653001400055653001600069653001800085653003200103653002600135653002100161100001800182700002900200700001600229700001800245245009400263856005800357300001000415490000600425520197200431022001402403       2024                            d  c03/202410aEducation10aCybernetics10aGenerative AI10aHuman-Machine Communication10aLarge Language Models10aMachine Learning1 aDai Griffiths1 aEnrique Frías-Martínez1 aAhmed Tlili1 aDaniel Burgos00aA Cybernetic Perspective on Generative AI in Education: From Transmission to Coordination  uhttps://www.ijimai.org/journal/bibcite/reference/3430  a15-240 v83 aThe 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.  a1989-1660