Predicción de ranking de asignaturas a partir de resultados académicos

Abstract

[en] This final degree project is part of a teaching innovation project (PID), it aims to create an "intelligent support system for tutor studies" based on a data science analysis of academic results. The system will help the tutor to make better decisions in their work of supervision and guidance to their students. The project was launched 3 years ago, some students of the Faculty of Mathematics and Computing worked and contributed in several aspects. The work that’s going to be done in this project will be a continuation. It will mainly focus on the implementation of a variation of the prediction of subject ranking. The ranking of subjects will consist of ordering the subjects, depending on their difficulty. That is, the qualifications of the subjects of the following course for a student are predicted, using the qualifications of the subjects studied up to the moment. Based on these qualifications, it is deduced which subjects will be more “difficult” for the student. It will also be involved in the data analysis. More specifically, in inspecting the different ways in which the data could be treated to manage the missing values, with the expectation that the prediction accuracy could improve. Finally, the aim is to organize the code through the MVC structure, so that it can become more standardized.