APPLICATION OF CLUSTER ANALYSIS AS A TOOL TO ANALYSE DISTANCE EDUCATION STUDENTS
Anurag Saxena1, Pankaj Khare2, Suresh Garg3, Indira Gandhi National Open University, New Delhi, India
Asian Journal of Distance Education Volume 2, Number 2 ISSN 1347-9008
The educational databases often have hidden knowledge about the students, their academic behavior, their study skills and their performance in an academic program. This explicit knowledge (Koulopoulos and Frappaolo, 1999) can be used to facilitate learning more effectively and efficiently by the educational institutions. There are many studies that tried to analyse students’ characteristics and then draw conclusions about the students. These studies were mainly based on either nominal and interval data and the characteristic were judged by the percentage of students possessing these characteristics. Almost negligible number of studies tried to analyse students globally with respect to all their characteristics. Question thus arises that can students be classified on the basis of knowledge delivered by the student database. One of the data mining techniques of structuring data is “cluster analysis”. Clustering literally means, “to gather” or “draw together”. In terms of data, clustering means dividing the data in such a way that similar data points comes together.
Saxena1, A., Khare2, P. & Garg3, S. APPLICATION OF CLUSTER ANALYSIS AS A TOOL TO ANALYSE DISTANCE EDUCATION STUDENTS. Asian Journal of Distance Education, 2(2),.
ReferencesView References & Citations Map
These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.Suggest Corrections to References