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https://www.innovacioneducativa.unam.mx:8443/jspui/handle/123456789/8047
Título : | Diseño y validación de una herramienta para el análisis y predicción de la innovación metodológica en centros de educación secundaria a través del aprendizaje automático |
Autor : | Cabeza, Fernando Díaz, José L Sánchez, Almudena Roa, Julián |
Fecha de publicación : | 2024 |
Resumen : | Abstract: The primary objectives of this research study are to provide a detailed description of machine learning (ML) technology when applied to assessing innovation and to design a model that allows predicting an institution’s degree of innovation. Machine learning technology lacks assumptions or preconceptions and is capable of processing a large amount of data and variables. After data processing, the ML model is built using variables associated with educational context, training is performed, and a web is built to predict the degree of innovation of an educational institution. This model provides an innovation accuracy prediction of 66% and allows assessing the influence of the variables analyzed when predicting the use of active methodologies at a given institution. In conclusion, this approach can open new data analysis techniques supported by ML that complement traditional statistically based approaches. |
URI : | https://www.innovacioneducativa.unam.mx:8443/jspui/handle/123456789/8047 |
ISSN : | 0718-0764 |
metadata.dc.identifier.url: | https://www.scielo.cl/pdf/infotec/v35n4/0718-0764-infotec-35-04-37.pdf |
metadata.dc.type: | journalArticle |
Aparece en las colecciones: | Artículos científicos y académicos |
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