title: Data-driven system to predict academic grades and dropout.
abstract: Nowadays, the role of a tutor is more important than ever to prevent students dropout and improve their academic performance. This work proposes a data-driven system to extract relevant information hidden in the student academic data and, thus, help tutors to offer their pupils a more proactive personal guidance. In particular, our system, based on machine learning techniques, makes predictions of dropout intention and courses grades of students, as well as personalized course recommendations. Moreover, we present different visualizations which help in the interpretation of the results. In the experimental validation, we show that the system obtains promising results with data from the degree studies in Law, Computer Science and Mathematics of the Universitat de Barcelona.
authors.affiliation: Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007 Barcelona (Spain).
authors.forename: Sergi
authors.initials: S
authors.lastname: Rovira
authors.affiliation: Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007 Barcelona (Spain).
authors.forename: Eloi
authors.initials: E
authors.lastname: Puertas
authors.affiliation: Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007 Barcelona (Spain).
authors.forename: Laura
authors.identifier: http://orcid.org/0000-0002-7225-7441
authors.initials: L
authors.lastname: Igual
mesh_terms: D000293:Adolescent; D000328:Adult; D005260:Female; D006801:Humans; D000069550:Machine Learning; D008297:Male; D008962:Models, Theoretical; D013332:Student Dropouts