SPEET: visual data analysis of engineering students performance from academic data
Manuel Domínguez, Ramón Vilanova, Miguel Angel Prada, José López Vicario, Marian Barbu, Maria João Varanda Pereira, Michał Podpora, Umberto Spagnolini, Paulo Alexandre Alves, Anna Maria Paganoni · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2018
This paper presents the steps conducted to design and develop an IT Tool for Visual Data Analysis within the SPEET (Student Profile for Enhancing Engineering Tutoring) ERASMUS+ project. The global goals of the project are to provide insight into student behaviours, to identify patterns and relevant factors of academic success, to facilitate the discovery and understanding of profiles of engineering students, and to analyse the differences across European institutions. Those goals are partly covered by the visualisations that the proposed tool comprises. Specifically, the aim is to provide support to the staff involved in tutoring, facilitating the exploratory analysis that might lead them to discover and understand student profiles. For that purpose, visual interaction and two main approaches are used, one based on the joint display of interconnected visualisations and the other focused on dimensionality reduction. The tool is validated on a data set that includes variables present in a typical student record.