SPEET: an international collaborative experience in data mining for education

This paper presents the collaborative experience that is under development as the European ERASMUS+ project SPEET (Student Profile for Enhancing Engineering Tutoring). This project goal emerges from the potential synergy among a) the huge amount of academic data actually existing at the academic departments of faculties and schools, and b) the maturity of data science in order to provide algorithms and tools to analyse and extract information from the available large amount of data. A rich picture can be extracted from this data if conveniently processed. The main purpose of this project is to apply data mining algorithms to process this data in order to extract information about and to identify student profiles. Some examples of the student profile we are referring to within the project scope is, for example: Students that finish degree on time, Students that are blocked on a certain set of subjects, Students that leave degree earlier, etc

Keywords

Educational data mining Drop-off Tutoring action support

URI

http://hdl.handle.net/10198/19343

Citation

Vilanova, Ramon; Vicario, José; Prada, Miguel; Barbu, Marian; Dominguez, Manuel; Pereira, Maria João; Podpora, Michal; Spagnolini, Umberto; Alves, Paulo; Paganoni, Anna (2017). SPEET: an international collaborative experience in data mining for education. In 110th International Conference of Education, Research and Innovation (ICERI2017). Seville