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Data Mining Application for Distance Education Information System
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NSTL
Distance education is organised in three main forms: asynchronous, synchronous and blended. Student's data for analysis will be used only the asynchronous learning portion of the information system, since this portion is already used in master's studies for a considerable time, and a sufficient amount of data has been accumulated. Data mining technology can help to find interesting and useful patterns in huge volume of data. Data analysis will be performed on the data of master students and bachelor students as well, that can learn in 11 e-courses. Clustering technique was used for user's data analysis which is fitting best when we know nothing about them. After clustering database we have got nine clusters and that's clusters' interpretation, which let us to except typical student's behaviours.
NSTL
