Visualizing Student Performances Using Data Mining Techniques.

The goal of this qualitative paper is to conduct a study to visualize the student performances where the input data is the student's result and the output of the information retrieved is displayed in a graphical representation. The study focuses on identifying the factors that influence the st...

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Main Author:	Sri Banu, Munisamy
Format:	Thesis
Language:	eng eng
Published:	2007
Subjects:	QA76 Computer software
Online Access:	https://etd.uum.edu.my/39/1/sri_banu.pdf https://etd.uum.edu.my/39/2/sri_banu.pdf
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id	my-uum-etd.39
record_format	uketd_dc
spelling	my-uum-etd.392013-07-24T12:05:24Z Visualizing Student Performances Using Data Mining Techniques. 2007 Sri Banu, Munisamy Sekolah Siswazah Graduate School QA76 Computer software The goal of this qualitative paper is to conduct a study to visualize the student performances where the input data is the student's result and the output of the information retrieved is displayed in a graphical representation. The study focuses on identifying the factors that influence the student performances as well as visualizing the result for management's convenience. The approach that has been used to categorize the influencing variables is factor analysis. The analysis and visualization has been done using SPSS. Result of the analysis shows that student attitude and lecturer's background are the two factors most important factor known to influence students' performances. 2007 Thesis https://etd.uum.edu.my/39/ https://etd.uum.edu.my/39/1/sri_banu.pdf application/pdf eng validuser https://etd.uum.edu.my/39/2/sri_banu.pdf application/pdf eng public masters masters Universiti Utara Malaysia Basu, S. (1997) DATA MINING. Georgia State University Fall Retrieved 21 February 2007 from http://www.siggraph.org/education/materialslHyperVis/applicat/data_mining/data_mining.html Cooper, D.R., & Schindler, P.S. (2006) Business Research Methods. New York: McGraw- Hill/Irwin. Edwards,S.H., Perez-Quinones,M.A., Phillips,M., & RajKumar,J.(2006) Graphing performance on programming assignments to improve student understanding. In Proceedings of the International Conference on Engineering Education Fayyad,U., Piatetsky-Shapiro,G., & Smyth,P.(1996) The KDD process for extracting useful knowledge from volumes of data. In Communications of the ACM{Data Mining and Knowledge Discovery in Databases Fayyad,U., Piatetsky-Shapiro,G., & Smyth,P.(1996) From data mining to knowledge discovery: An overview. In U.M. Fuyyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusanzy, editors, Advances in Knowledge Discovery and Data Mining, pages l{35. AAAI/MIT Press Fayyad,U. & Uthurusamy,R. (1999). Data mining and knowledge discovery in databases: Introduction to the special issue.Communications of the ACM, 39(11) George, D., & Mallery, P. (2003). SPSS for Windows Step by Step: A simple Guide and Reference. Pearson Education. Jing Luan (2004). Data mining applications in higher education, SPSS Executive Report. Keim,D.A, & Kriegel,H.(1996) Visualization techniques for mining large databases: A comparison. IEEE Transactions on Knowledge and Data Engineering Mazza,R., & Dimitrova,V. (2004) Visualising Student Tracking Data to Support Instructors in Web-Based Distance Education. 13th International World Wide Web Conference (WWW 2004) - Alternate Educational Track. 2004 May 17-22. pp. 154-161. Merceron,A., & Yacef, K. (2005). Educational Data Mining: a Case Study Minaei-Bidgoli,B., Kashy,D.A., Kortemeyer,G., & Punch,W.F. (2003). Predicting student performance: an application of data mining methods with the educational web-based system. LON-CAPA. Proceedings of ASEE/IEEE Frontiers in Education Conference
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA76 Computer software
spellingShingle	QA76 Computer software Sri Banu, Munisamy Visualizing Student Performances Using Data Mining Techniques.
description	The goal of this qualitative paper is to conduct a study to visualize the student performances where the input data is the student's result and the output of the information retrieved is displayed in a graphical representation. The study focuses on identifying the factors that influence the student performances as well as visualizing the result for management's convenience. The approach that has been used to categorize the influencing variables is factor analysis. The analysis and visualization has been done using SPSS. Result of the analysis shows that student attitude and lecturer's background are the two factors most important factor known to influence students' performances.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Sri Banu, Munisamy
author_facet	Sri Banu, Munisamy
author_sort	Sri Banu, Munisamy
title	Visualizing Student Performances Using Data Mining Techniques.
title_short	Visualizing Student Performances Using Data Mining Techniques.
title_full	Visualizing Student Performances Using Data Mining Techniques.
title_fullStr	Visualizing Student Performances Using Data Mining Techniques.
title_full_unstemmed	Visualizing Student Performances Using Data Mining Techniques.
title_sort	visualizing student performances using data mining techniques.
granting_institution	Universiti Utara Malaysia
granting_department	Sekolah Siswazah
publishDate	2007
url	https://etd.uum.edu.my/39/1/sri_banu.pdf https://etd.uum.edu.my/39/2/sri_banu.pdf
_version_	1747826832285106176

Visualizing Student Performances Using Data Mining Techniques.

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