Dropout and transfer paths: What are the risky profiles when analyzing university persistence with machine learning techniques?-Reference-Cited by-同舟云学术

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Dropout and transfer paths: What are the risky profiles when analyzing university persistence with machine learning techniques?

Published:2019-06-21 Issue:6 Volume:14 Page:e0218796
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Rodríguez-Muñiz Luis J.^ORCID,Bernardo Ana B.^ORCID,Esteban María^ORCID,Díaz Irene

Funder

Consejería de Empleo, Industria y Turismo, Principado de Asturias (ES)

Ministerio de Educación (ES)

Ministry of Science, Innovation and Universities

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference55 articles.

1. Higher Education Drop-Out in Spain—Particular Case of Universities in Galicia;ME Arce;IES,2015

2. The Influence of Active Learning on the College Student Departure Process: Toward a Revision of Tinto's Theory;JM Braxton;J High Educ,2000

3. Higher Education: Handbook of theory and research;V Tinto,1986

4. Leaving college: Rethinking the causes and cures of student attrition;V Tinto,1993

5. The Nexus between College Choice and Persistence;EP St John;Res High Educ,1996

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5. Compensatory advantage after the first year at university in the Catalan system: between continuing, transferring and dropping out;Studies in Higher Education;2023-11-10

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