An intelligent system for guiding the use of dynamic concept maps in the zone of proximal development

With reference to the theory of the Zone of Proximal Development, the aim of this paper is to describe an intelligent tutoring model capable of learning and reproducing intervention rules to make learning experiences based on the use of dynamic concept maps more effective. The work starts from DCMapp, a software application for the creation and navigation of dynamic concept maps. DCMapp allows to build maps, draw nodes and arcs, upload multimedia contents and manage the dynamic visualization of concepts. The use of DCMapp has been shown to improve study times and student learning outcomes. The paper proposes the integration of an intelligent tutoring system based on Vygotsky’s theory of the Zone of Proximal Development. This system suggests actions to students to maintain learning within their Zone of Proximal Development, avoiding boredom and confusion. It is trained through the observation of a human tutor and uses artificial neural networks to predict future actions. The goal is to ensure effective and personalized learning, adapting the difficulty of the activities to the cognitive and emotional abilities of the learners.