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. The project will use AI to create a system that will be able to preventively detect academic students who are at risk for academic dropout. Using machine learning algorithms, the project will be 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 (during the first year of university). The project will result in a new integrated system for academic tutoring services who would then be able to: - preventively detect students at risk of dropout. - profiling the different students at risk based on the specific issues they might be facing. - offer personalized services and tools that match the students’ needs. - offer training to tutors and academic institutions to enable them to optimally use the system and the services created within the project. The consortium will base this project on previous literature on academic dropout and on some relevant existing initiatives and best experiences in the field of digital technologies for career guidance (based on the results of the Etutoring project, LEADER project and MYFUTURE project). The project will also promote a wide and open use of digital tools as recommended in the 2013 EU Communication on Opening Up Education. The main innovative points are: • The use of AI techniques in the field of education. • The use of AI with a preventive approach. • A preventive approach in the field of higher education to optimize resources and services. • The direct involvement of researchers, experts, career guidance practitioners, students and tutors for a joint design and implementation of innovative interventions to help students in their academic journey. • The use of co-design techniques and design thinking methodologies. • The creation of open resources for supporting interventions to prevent academic dropouts. The intellectual outputs will be: - Toolkit for tutors and practitioners: reference framework for academic career guidance practitioners; - STAR.APP online platform for risk assessment: matching the future for your success; - Handbook: New frontiers for preventing academic dropout.
The achievements reached by means of the implementation of the project will be: - preventively detect students at risk of dropout. - profiling the different students at risk based on the specific issues they might be facing. - to offer personalized services and tools that match the students’ needs. - to offer training to tutors and academic institutions to enable them to optimally use the system and the services created within the project.
The main aim of the project was to create a system that will be able to preventively detect academic students who are at risk for academic dropout and, at the same time, increasing academic attainment across European countries by means of AI algorithms. There is a great amount of students specially in the first year of University in risk of dropout, as it can be read in many reports and documents from European institutions and others. Definition of profiles of students at risk at the beginning of the academic year and development of new preventive interventions specifically targeting these students was the main need detected.