A Module Based on Data Mining Techniques to Analyze School Attendance Patterns of Children with Disabilities in Cañar - Ecuador

Denys Dutan-Sanchez, Paúl Idrovo-Berrezueta, Ana Parra-Astudillo, Vladimir Robles-Bykbaev, María Ordóñez-Vásquez

Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

According to UNICEF, 24% of children with disabilities are less likely to receive early stimulation, whereas 49% are more likely to have never attended school. For these reasons, it is essential to provide early stimulation tools for children with disabilities living in developing countries. In this paper, we describe a module based on data mining techniques to determine the children’s school attendance. To train the algorithms we collected data of 245 children that received early stimulation and therapy in the Special School “Jesus for the Children” of the city of Cañar - Ecuador during the last 26 years. The preliminary results show that the analysis module can classify children according to their attendance patterns with 85% of precision.

Idioma originalInglés
Título de la publicación alojadaInformation Technology and Systems - ICITS 2023
EditoresÁlvaro Rocha, Carlos Ferrás, Waldo Ibarra
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas451-461
Número de páginas11
ISBN (versión impresa)9783031332579
DOI
EstadoPublicada - 2023
EventoInternational Conference on Information Technology and Systems, ICITS 2023 - Cusco, Perú
Duración: 24 abr. 202326 abr. 2023

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen691 LNNS

Conferencia

ConferenciaInternational Conference on Information Technology and Systems, ICITS 2023
País/TerritorioPerú
CiudadCusco
Período24/04/2326/04/23

Nota bibliográfica

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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