El impacto de la IA en el aprendizaje basado en problemas y el pensamiento variacional

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Mathematics education is essential to prepare citizens for the challenges of the 21st century, in particular to develop Variational Thinking and the ability to solve problems in the educational field. However, it faces challenges such as lack of motivation in students and understanding abstract concepts complicated by the variety of learning styles. Consequently, through technological advancement, Artificial Intelligence (AI) has introduced as a tool to personalize teaching and improve learning, although this poses additional challenges, such as data privacy and possible algorithmic biases. In this context, studies have found that highlight the need for a unifying approach in Mathematics Education, emphasizing the potential of AI to overcome these difficulties, especially in complex areas such as Differential Calculus. The purpose of this research is to evaluate the impact of AI in mathematics teaching, focusing on improving learning by using Problem-Based Learning (PBL) and Variational Thinking. Through a systematic review based on the PRISMA method, empirical studies published between 2019 and 2024, where they investigate the application of AI in the educational field. The results show that AI integration has significantly improved both academic performance and student motivation, although challenges remain in its effective implementation, the need for teacher training and the moderation of risks associated with technology.

This publication has 43 references indexed in Scilit: