University of Tabriz Journal of Philosophical Investigations 2251-7960 Articles in Press 2026 06 03 From Syllogism to Simulation: AI and the Transformation of Reasoning in Education From Syllogism to Simulation: AI and the Transformation of Reasoning in Education 21676 10.22034/jpiut.2026.71974.4469 FA Sumanta Sarathi Sharma School of Philosophy & Culture Shri Mata Vaishno Devi University, Jammu, India Satish Kumar Tiwari Head of Department, Department of Philosophy, Government P.G. College, Agasyamuni, Rudraprayag , Uttarakhand Journal Article 2026 04 15 This paper examines how the growing use of artificial intelligence (AI) in education is reshaping not only how students learn, but also what it means to reason. Drawing on the tradition of syllogistic reasoning, from Aristotle’s logic to later diagrammatic developments, it highlights that reasoning has historically been understood as an active process of grasping why conclusions follow from given premises. In contrast, contemporary AI systems can produce answers that resemble reasoning, yet they do so without genuine understanding. Also, in this paper, we argue that this shift encourages a move from understanding-based reasoning to output-oriented reasoning, where the emphasis is placed on obtaining answers rather than engaging with the reasoning process itself. In this sense, AI does not simply assist reasoning but can begin to displace it, turning it into something externally performed rather than internally developed. While recognizing the advantages AI offers in terms of efficiency and access to information, the paper raises concerns about over-reliance, including the risk of superficial learning and a misplaced sense of competence. By engaging with debates in philosophy of mind and education, it ultimately calls for a more balanced approach, one that integrates AI thoughtfully while preserving the central role of human understanding in reasoning and learning. This paper examines how the growing use of artificial intelligence (AI) in education is reshaping not only how students learn, but also what it means to reason. Drawing on the tradition of syllogistic reasoning, from Aristotle’s logic to later diagrammatic developments, it highlights that reasoning has historically been understood as an active process of grasping why conclusions follow from given premises. In contrast, contemporary AI systems can produce answers that resemble reasoning, yet they do so without genuine understanding. Also, in this paper, we argue that this shift encourages a move from understanding-based reasoning to output-oriented reasoning, where the emphasis is placed on obtaining answers rather than engaging with the reasoning process itself. In this sense, AI does not simply assist reasoning but can begin to displace it, turning it into something externally performed rather than internally developed. While recognizing the advantages AI offers in terms of efficiency and access to information, the paper raises concerns about over-reliance, including the risk of superficial learning and a misplaced sense of competence. By engaging with debates in philosophy of mind and education, it ultimately calls for a more balanced approach, one that integrates AI thoughtfully while preserving the central role of human understanding in reasoning and learning.