| 000 | 01818naa a2200253 a 4500 | ||
|---|---|---|---|
| 003 | AR-LpUFIB | ||
| 005 | 20250311171146.0 | ||
| 008 | 230201s2015 xx o 000 0 eng d | ||
| 024 | 8 |
_aDIF-M7311 _b7527 _zDIF006672 |
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| 040 |
_aAR-LpUFIB _bspa _cAR-LpUFIB |
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| 100 | 1 | _aLanzarini, Laura Cristina | |
| 245 | 1 | 0 | _aAcademic performance of university students and its relation with employment |
| 300 | _a1 archivo (301.7 KB) | ||
| 500 | _aFormato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca) | ||
| 520 | _aEducational Data Mining collects the various methods that allow extracting novelty and useful information from large data volumes in educational contexts. This paper describes the process used to, through Data Mining techniques, identify the most relevant characteristics in relation to student academic performance at the School of Computer Science of the National University of La Plata. The results obtained using the proposed method to process the information relating to regular and non-regular students at the UNLP allowed establishing interesting relationships in relation to student academic performance. Based on the obtained models it can be said that the fact that the student works does not mean that their academic performance decrease and young students that take several years to join the faculty have better performance if they express interest in getting a job. | ||
| 534 | _aLatin American Computing Conference (41st : 2015 oct. 19-23 : Arequipa, Perú) | ||
| 650 | 4 | _aMINERÍA DE DATOS | |
| 650 | 4 | _aINTERNET | |
| 650 | 4 |
_aEDUCACIÓN _91801 |
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| 700 | 1 |
_aDíaz, Francisco Javier _94623 |
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| 700 | 1 | _aCharnelli, María Emilia | |
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1109/CLEI.2015.7360017 |
| 942 | _cCP | ||
| 999 |
_c56449 _d56449 |
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