View Item 

Rough sets for mining educational data

View/Open
Access Status
Open access
Authors
Johnson, J.
Johnson, Genevieve
Cavanagh, Rob
Date
2012
Type
Conference Paper
Metadata
Show full item record
Abstract

While educational data are typically analyzed with statistical software, data mining techniques are increasingly appropriate in revealing complex relationships among multiple variables in large amounts of data. We experimented with the rough set method in conjunction with statistical analysis to identify patterns in, and thereby extract meaning from, complex educational data. Results establish the benefits of combining rough set decision making with stochastic analysis in mining exceedingly complex and difficult to interpret educational data sets.

Citation
Johnson, Julia Ann and Johnson, Genevieve Marie and Cavanagh, Robert F. 2012. Rough sets for mining educational data, in Proceedings of the 2012 Spring World Congress on Engineering and Technology (SCET 2012): Sharing, Cooperating and Improving, May 27-30 2012, pp. 131-134. Xi'an, China: Institute of Electrical and Electronic Engineers.
Source Title
Proceedings of the Spring World Congress on Engineering and Technology
URI
DOI
Remarks

NOTICE: This is the author’s version of a work in which changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication.

Copyright © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Collections