Desarrollo de un componente de moodle con inteligencia artificial para el análisis y predicción de datos educativos que permitan contribuir a la mejora de la calidad del proceso enseñanza-aprendizaje.

Abstract

Poor academic performance is a recurring factor within the educational area; over the decades it has positioned itself as a multifactorial problem, whose intervention is imperative to ensure the correct insertion of students within such a competitive and changing community. Faced with this problem, the present project proposes the development of an API component for the Moodle virtual learning platform, integrating Machine Learning techniques to, based on the records present within the course database, make predictions on various parameters of the students oriented to possibly present at the end of the course. For this, the correct analysis of the information, detection of parameters and trends in the behavior of individuals for the correct generation of speculations is relevant. In turn; taking advantage of the valuable information obtained through this process; automatic and personalized recommendations will be generated, which will be intended for teachers and students. Early intervention is essential since it can be critical in the treatment with the patient; offering multiple benefits before the problematic career has the relevant problems.. For all these reasons, the use of these new artificial intelligence technologies can become a fundamental and constant pillar within the educational area; since having such valuable information in advance can be crucial and of great benefit for decision-making for both the teacher and the students, allowing for the improvement of the performance of the teaching-learning process.