Adaptive Learning App for ADHD in Lima Schools

• Autores: Del Pino Herrera, Carlos David, Pinedo Solis, Emilio Adolfo, Herrera Trujillo, Emilio Antonio
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad Peruana de Ciencias Aplicadas
• Repositorio: UPC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorioacademico.upc.edu.pe:10757/676079
• Enlace del recurso: http://hdl.handle.net/10757/676079
• Nivel de acceso: acceso embargado
• Materia: ADHD; children; Educational method; Lima; machine learning; mindfulness; random forest; student

Education is fundamental for all children, but those with neurological disorders, such as attention deficit hyperactivity disorder (ADHD), have specific learning needs that are not addressed by traditional educational methods. This project focuses on the creation of a mobile application that employs machine learning algorithms to evaluate the progress of these children through regression methods, focusing on mathematical problem solving in elementary schools in Lima. Results have shown that this initiative has improved the understanding and performance of children with ADHD, highlighting the potential of mobile technology and machine learning to move towards a more inclusive and effective education for this group of students. This project has proven to be a valuable tool in the educational field. The inclusion of technological tools such as the mobile app has allowed personalization in teaching, adapting the content and pace of learning to the individual needs of each student with ADHD. In addition, the use of machine learning has enabled a continuous and accurate monitoring of their progress, identifying areas for improvement early on.