| dc.creator | La Red Martínez, David Luis | |
| dc.creator | Giovannini, Mirtha | |
| dc.creator | Karanik, Marcelo | |
| dc.date | 2020-05-29T15:06:43Z | |
| dc.date | 2020-05-29T15:06:43Z | |
| dc.date | 2018-12-01 | |
| dc.date.accessioned | 2023-08-31T14:11:29Z | |
| dc.date.available | 2023-08-31T14:11:29Z | |
| dc.identifier | 2315-7704 | |
| dc.identifier | http://hdl.handle.net/20.500.12272/4439 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8546612 | |
| dc.description | It is well known that academic achievement is one of the key aspects in the
development of educational activities and it strongly determines the chances of
success during and after a university career. It is therefore important to try and
effectively monitor students’ performance in order to prevent problems from
emerging, as well as, to be able to provide academic coaching when the
performance is not adequate. The aforementioned problem-anticipation
possibility is closely related to the ability to predict the most probable situation
based on concrete information. In an academic achievement framework, it is
desirable to be able to predict students’ performance considering concrete
individual parameters. This work outlines the results obtained by an academicachievement prediction model based on data mining algorithms which uses socioeconomic information as well as, students’ grades. The tests were carried out at National Technological University, Resistencia Regional Faculty (UTN-FRRe), during the AED-Algoritmos y Estructuras de Datos (Algorithms and Data Structures) class throughout the 2013, 2014, 2015 and 2016 terms. The results obtained confirmed adequate behaviour of the model which has been validated for both description and prediction of academic achievement profiles. | |
| dc.description | Fil: La Red Martínez, David Luis. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina | |
| dc.description | Fil: Giovannini, Mirta Eve. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina | |
| dc.description | Fil: Karanik, Marcelo. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina | |
| dc.description | Peer Reviewed | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.language | eng | |
| dc.relation | Diseño de un modelo predictivo de rendimiento académico mediante la utilización de minería de datos. Director del proyecto: Dr. David L. La Red Martínez | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.rights | Atribución-NoComercial-CompartirIgual 4.0 Internacional | |
| dc.rights | Acceso abierto | |
| dc.source | Academia Journal of Educational Research 6(12), 279-289. (2018) | |
| dc.subject | academic achievement | |
| dc.subject | student profiles | |
| dc.subject | data mining | |
| dc.subject | machine learning | |
| dc.title | Academic performance profiles: An intelligent predictive model based on data mining | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
