Mostrar el registro sencillo del ítem
dc.contributor.author
Musso, Mariel Fernanda
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.contributor.author
Rodríguez Hernández, Carlos Felipe
dc.contributor.author
Cascallar, Eduardo C.
dc.date.available
2020-07-23T21:09:24Z
dc.date.issued
2020-03
dc.identifier.citation
Musso, Mariel Fernanda; Rodríguez Hernández, Carlos Felipe; Cascallar, Eduardo C.; Predicting key educational outcomes in academic trajectories: a machine-learning approach; Springer; Higher Education; 3-2020
dc.identifier.issn
0018-1560
dc.identifier.uri
http://hdl.handle.net/11336/110124
dc.description.abstract
Predicting and understanding different key outcomes in a student's academic trajectory such as grade point average, academic retention, and degree completion would allow targeted intervention programs in higher education. Most of the predictive models developed for those key outcomes have been based on traditional methodological approaches. However, these models assume linear relationships between variables and do not always yield accurate predictive classifications. On the other hand, the use of machine-learning approaches such as artificial neural networks has been very effective in the classification of various educational outcomes, overcoming the limitations of traditional methodological approaches. In this study, multilayer perceptron artificial neural network models, with a backpropagation algorithm, were developed to classify levels of grade point average, academic retention, and degree completion outcomes in a sample of 655 students from a private university. Findings showed a high level of accuracy for all the classifications. Among the predictors, learning strategies had the greatest contribution for the prediction of grade point average. Coping strategies were the best predictors for degree completion, and background information had the largest predictive weight for the identification of students who will drop out or not from the university programs.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
MACHINE LEARNING
dc.subject
HIGHER EDUCATION
dc.subject
PREDICTION
dc.subject
EDUCATIONAL ACHIEVEMENT
dc.subject.classification
Psicología
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
Psicología
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
CIENCIAS SOCIALES
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.title
Predicting key educational outcomes in academic trajectories: a machine-learning approach
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-07-01T17:03:27Z
dc.identifier.eissn
1573-174X
dc.journal.pais
Suiza
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.description.fil
Fil: Musso, Mariel Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental "Dr. Horacio J. A. Rimoldi". Grupo Vinculado CIIPME - Entre Ríos - Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental "Dr. Horacio J. A. Rimoldi"; Argentina
dc.description.fil
Fil: Rodríguez Hernández, Carlos Felipe. Katholikie Universiteit Leuven; Bélgica
dc.description.fil
Fil: Cascallar, Eduardo C.. Katholikie Universiteit Leuven; Bélgica
dc.journal.title
Higher Education
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s10734-020-00520-7
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1007/s10734-020-00520-7
Archivos asociados