Research
STudent's Academic perfoRmance: a machine learning APProach for risk assessment and drop out prevention
Name of project: STudent's Academic perfoRmance: a machine learning APProach for risk assessment and drop out prevention
Acronym: STAR.APP
Refrence nr./contract nr.: 2020-1-ES01-KA203-082090
Project website/link: /
Project funding/programme:

Time frame:1.9.2020- 31.12.2022
Total costs: 235.095,00 EUR
Co-funding rate (in %): 0%
The amount of co-financing (UM FERI share): 27.160,00 EUR
UM FERI Coordinator: doc. dr.Sašo Karakatič
Project Coordinator: Universidad de Zaragoza
Other partners: Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko (UM FERI, SLO), Centro Studi Pluriversum Srl (Spain), Universidad De Zaragoza (Spain), Universita Degli Studi Di Camerino (Italy), Edex - Educational Excellence Corporation Limited (Cyprus), Viesoji Istaiga Socialiniu Mokslu Kolegija (Lithuania)
Project summary:
The cooperation will explore the potentials of Artificial Intelligence (AI) in the field of Higher Education with the aim of decreasing academic dropout and increasing academic attainment across European countries. Using machine learning algorithms, the system is able to define profiles of students at risk at the beginning of the academic year and, with a co-design approach, will then develop new preventive interventions specifically targeting the students at risk of dropout.
UM FERI activities:
The development of the AI system.