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.Sa┼ío Karakati─Ź

Project Coordinator: Universidad de Zaragoza

Other partners: Univerza v Mariboru, Fakulteta za elektrotehniko, ra─Źunalni┼ítvo 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.