Identification and comparison of the main variables affecting early university dropout rates according to knowledge area and institution

Alba Llauró, David Fonseca, Susana Romero, Marian Aláez, Jorge Torres Lucas, María Martínez Felipe

Research output: Indexed journal article Articlepeer-review

1 Citation (Scopus)

Abstract

The dropout rate in universities is a widely studied issue that concerns both universities and public organizations. Most studies focus on quantifying the phenomenon and identifying the variables involved. This paper uses a multidisciplinary approach to parameterize the factors that define the entry profile of undergraduates at the national level in Spain in collaboration with three universities in different regions and with different disciplines. The aim is to reduce the dropout rate in the first year of study towards a degree. The research questions focus on the weighting of personal variables about students by tutors and whether there are differences in the weighting systems for the main variables as differentiated by discipline, university and/or region. The document is organized to describe the method and context of the study, present the main results, show the application of the survey instrument in a case study, and provide conclusions. The method is based on the two fundamental factors, including the influence of certain student characteristics at matriculation and the importance of a positive experience in the first year of the degree. The study is focused on two elements that inspire the current proposal: the need to identify and rapidly detect students who, due to their entry characteristics, are at a greater risk of dropout and the importance of guaranteeing a good start in the first year of the degree. The study uses a multidisciplinary approach and combines qualitative and quantitative methods to gather data. The study also uses a survey instrument that measures the risk of student dropout based on the weighting of personal variables by tutors. The results of the study have allowed us to categorize the main variables of the student profile that affect the risk of dropout and establish them as aspects to be monitored by the tutors in the first weeks. Furthermore, it has been shown that although there are no significant differences in the averages of dropout risk calculated with either global or specific weighting systems (by centre or studies), there is a tendency observed by the tutors that the weighted averages generated by disciplinary focus are closer to identifying the student's real risk of dropping out.

Original languageEnglish
Article numbere17435
Number of pages16
JournalHeliyon
Volume9
Issue number6
DOIs
Publication statusPublished - Jun 2023

Keywords

  • Academic analytics
  • Early dropout
  • First-year students
  • Learning analytics
  • Predictions
  • Tutoring

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