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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cartuche Flores, C. | es_ES |
dc.contributor.author | Gomez Alvarado, H. | es_ES |
dc.contributor.author | Arias Tapia, S. | es_ES |
dc.contributor.author | Malo Martinez, S. | es_ES |
dc.date.accessioned | 2017-06-16T22:02:24Z | - |
dc.date.available | 2017-06-16T22:02:24Z | - |
dc.date.submitted | 10/04/2016 | es_ES |
dc.identifier | 10.1109/EDUCON.2016.7474710 | es_ES |
dc.identifier.isbn | 21659559 | es_ES |
dc.identifier.issn | 978-146738633-3 | es_ES |
dc.identifier.other | 10.1109/EDUCON.2016.7474710 | es_ES |
dc.identifier.uri | http://dspace.utpl.edu.ec/handle/123456789/18803 | - |
dc.description.abstract | The identification of academic attributes that allow improving student achievement is of fundamental importance in the teaching learning process. In the current study we present a methodology to recognize the attributes of educational success based Pareto distribution and data mining algorithms that authorize the identification of which attributes most important to child's educational performance. Our results showed the direct theoretical and numerical relationship between academic indicators and the proper selection of the milestones in the learning. Conclusions and future work will be generated from our working the same as is in the process of development. | es_ES |
dc.language | Inglés | es_ES |
dc.subject | Attributes | es_ES |
dc.subject | Metrics | es_ES |
dc.subject | Pareto | es_ES |
dc.title | A methodology for identifying attributes of academic excellence based on a 20/80 Pareto distribution | es_ES |
dc.type | Article | es_ES |
dc.publisher | 2016 IEEE Global Engineering Education Conference (EDUCON) | es_ES |
Appears in Collections: | Artículos de revistas Científicas |
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