ABSTRACT
Student dropout is a major concern in studies investigating higher education retention strategies. However, studies investigating the optimal time to identify students who are at risk of withdrawal and the type of data to be used are scarce. Our study consists of a withdrawal prediction analysis based on classification trees using both sociodemographic and academic data from 935 first-year students at an engineering school in Spain. We build prediction models using information collected at three different moments throughout the first semester of the students’ first university year. Our results echo those of previous studies supporting the need for an early first-year intervention to prevent non-completion. In addition, academic performance data serve as a good predictor. Finally, academic monitoring throughout the first semester improves the prediction accuracy, challenging the demand for ‘as soon as possible’ identification of students who are at risk of dropout.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. The HE admission grade in Spain is the weighted average grade of the two final school years’ results and the score obtained on the official university admission exam. Academic grades range from 0 to a maximum of 10, and ‘5ʹ is the passing grade.
Additional information
Notes on contributors
José María Ortiz-Lozano
José María Ortiz Lozano is the Director of the Registrar’s Office at Universidad Pontificia Comillas. He performs studies in the field of quality management and applies multivariate analysis techniques to study management.
Antonio Rua-Vieites
Antonio Rua Vieites is a lecturer at Universidad Pontificia Comillas. He lectures and performs quantitative methods studies in the fields of management and sociology.
Paloma Bilbao-Calabuig
Paloma Bilbao-Calabuig is a lecturer at Universidad Pontificia Comillas. She lectures and performs studies in the field of Corporate Governance and Sustainability and has published in journals such as Human Ecology Review.
Martí Casadesús-Fa
Marti Casadesus is a professor at the University of Girona. His studies focus on quality management and have been published in journals such as Total Quality Management, International Journal of Quality & Reliability Management, The TQM Magazine and International Journal of Operations & Management.