Academic Analytics Applied in the Study of the Relationship Between the Initial Profile of Undergraduate Students and Early Drop-Out Rates. Defining the Variables of a Predictor Instrument

Alba Llauró, David Fonseca, Daniel Amo-Filva, Susana Romero, Marian Aláez, Jorge Torres Lucas, María Martínez Felipe

Producción científica: Capítulo del libroCapítulorevisión exhaustiva

1 Cita (Scopus)

Resumen

The field of university dropout research is of utmost importance especially in the current context arising from the Covid-19 pandemic. Students who started their degrees in the last two years completed their pre-university studies during various phases of confinement and by combining traditional and virtual training. In this scenario, students' motivation and the way they cope with the difficulties of their first year of university are very relevant and will depend on a multitude of personal and social variables in their immediate environment. Previous studies have shown that many university students drop out of their studies early, but what factors and to what extent they affect this dropout is still a field under study. This paper focuses on the identification, classification and evaluation of a set of indicators based on teacher and tutor perception in different fields of study by applying quantitative and qualitative techniques. The results of pilot studies developed support the approach adopted, as they show how teachers can identify students at risk of dropping out at the beginning of the course and take proactive measures to monitor and motivate them, thus reducing the possibility of dropout.

Idioma originalInglés
Título de la publicación alojadaLecture Notes in Educational Technology
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas982-990
Número de páginas9
DOI
EstadoPublicada - 2023

Serie de la publicación

NombreLecture Notes in Educational Technology
ISSN (versión impresa)2196-4963
ISSN (versión digital)2196-4971

Huella

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