Early detection of students at dropout risk using administrative data and machine learning Detecção precoce de estudantes em risco de evasão usando dados administrativos e aprendizagem de máquina
| dc.contributor.author | Lopes Filho J.A.B. | |
| dc.contributor.author | Silveira I.F. | |
| dc.date.accessioned | 2024-03-12T19:23:26Z | |
| dc.date.available | 2024-03-12T19:23:26Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.High dropout rates are a serious and widespread problem in many countries around the globe, both in traditional and e-learning environments, in both private and public education. Higher rates tend to have a negative impact on all profiles involved: students, institutions and the general public; noting that, despite the student’s own loss of educational gain, there is also monetary loss to the system in question, social stigma and feelings of inadequacy that may be associated with such dropout, and loss of cultural, social and interpersonal spheres arising from educational processes. Therefore, early detection systems regarding school dropout have gained more prominence, especially regarding the possibility of being a framework for the elaboration of new public policies, while also helping to better understand the probable causes for this dropout. | |
| dc.description.firstpage | 480 | |
| dc.description.issuenumber | E40 | |
| dc.description.lastpage | 495 | |
| dc.description.volume | 2021 | |
| dc.identifier.issn | 1646-9895 | |
| dc.identifier.uri | https://dspace.mackenzie.br/handle/10899/34821 | |
| dc.relation.ispartof | RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao | |
| dc.rights | Acesso Restrito | |
| dc.subject.otherlanguage | Classification | |
| dc.subject.otherlanguage | Dropout prediction | |
| dc.subject.otherlanguage | Educational data mining | |
| dc.subject.otherlanguage | Machine learning | |
| dc.subject.otherlanguage | Supervised learning | |
| dc.title | Early detection of students at dropout risk using administrative data and machine learning Detecção precoce de estudantes em risco de evasão usando dados administrativos e aprendizagem de máquina | |
| dc.type | Artigo | |
| local.scopus.citations | 0 | |
| local.scopus.eid | 2-s2.0-85101936792 | |
| local.scopus.updated | 2024-05-01 | |
| local.scopus.url | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85101936792&origin=inward |