A methodology for identifying attributes of academic excellence based on a 20/80 Pareto distribution

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...

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Bibliographic Details
Published in:	2016 IEEE Global Engineering Education Conference (EDUCON) pp. 1207 - 1211
Main Authors:	Gomez A., Hector F., Arias T., Susana A., Martinez, S. Elena Malo, Hernandez, Victor, Guerrero, Javier Sanchez, Reinoso, Adriana
Format:	Conference Proceeding Journal Article
Language:	English
Published:	IEEE 01-04-2016
Subjects:	Algorithms Attributes Conferences Data mining Education Electronics Engineering education Filtering theory Learning Methodology Metrics Pareto Pareto optimality Signal to noise ratio Students
Online Access:	Get full text
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Summary:	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.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Conference-1 ObjectType-Feature-3 content type line 23 SourceType-Conference Papers & Proceedings-2
ISSN:	2165-9567
DOI:	10.1109/EDUCON.2016.7474710