Interaction between Artificial Intelligence and Neurocognitive Processes: Contributions of Intelligent Tutors to the Development of Understanding and Problem-Solving

Abstract

The incorporation of artificial intelligence into educational systems has brought about a significant transformation in teaching and learning processes, particularly through the development of intelligent tutors capable of dynamically adapting to learners’ cognitive characteristics. These technologies go beyond the automation of content by actively engaging with key neurocognitive processes such as sustained attention, working memory, learning self-regulation and strategic problem-solving, thereby fostering personalised and learner-centred educational experiences. From a cognitive neuroscience perspective, learning is understood as a dynamic process involving the integration of neural networks related to comprehension, reasoning and decision-making; within this framework, intelligent tutors stand out for their ability to provide immediate feedback, organise learning sequences aligned with the learner’s cognitive level, and deliver progressive forms of support that promote deep learning. The aim of this study is to critically examine the interaction between artificial intelligence and the neurocognitive processes involved in learning, based on an analytical documentary review of specialised scientific literature, following the PRISMA guidelines. The findings indicate that intelligent tutors function as cognitive mediators that influence how learners process, organise and apply knowledge, consolidating this field as an emerging line of research within contemporary education.