RT info:eu-repo/semantics/conferenceObject
T1 Time management and absenteeism: studying the students through machine learning
A1 Porras Alfonso, Santiago
A1 Sauvée, Athénaïs
A1 Puche Regaliza, Julio César
A1 Casado Yusta, Silvia
A1 Antón Maraña, Paula
A1 Pacheco Bonrostro, Joaquín
K1 Absenteeism
K1 Higher education
K1 Support vector machine
K1 Explainable artificial intelligence
K1 Shapley additive explanation
K1 Time management
K1 Empleo del tiempo
K1 Time management
AB Absenteeism in higher education is a problem that may involve institutional, economic,social, and individual consequences. The present work aims to analyse whether the waystudents manage their personal time could be an explanation for absenteeism rates.Authors used machine learning based methodology, combined with explainable artificialintelligence methods. This allowed them to design a two-levels analysis, it is to say froma global, and an individual perspective. Factors such as repeating a course have themost negative impact over class attendance. On the contrary, being able to submit anassignment before the deadline has the most positive impact over class attendance. Thekind of academic career, the place of living or the hobbies has also influence over theabsenteeism.
PB Editorial Universitat Politècnica de València
SN 978-84-13962-00-9
YR 2024
FD 2024-06
LK https://hdl.handle.net/10259/10939
UL https://hdl.handle.net/10259/10939
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 17-may-2026