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  5. THE POSSIBILITIES OF CLUSTERING LEARNING METHODS IN STUDENT EDUCATION
 
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THE POSSIBILITIES OF CLUSTERING LEARNING METHODS IN STUDENT EDUCATION

Journal
SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference
ISSN
1691-5887
Date Issued
2019
Author(s)
Grabusts, Pēteris 
Rezekne Academy of Technologies 
DOI
10.17770/sie2019vol5.3723
Abstract
Many educational courses operate with models that were previously available only in mathematics or other learning disciplines. As a possible solution, there could be the use of package IBM SPSS Statistics and Modeler in realization of different algorithms for IT studies. Series of research were carried out in order to demonstrate the suitability of the IBM SPSS for the purpose of visualization of various simulation models of some data mining disciplines – particularly cluster analysis. Students are very interested in modern data mining methods, such as artificial neural networks, fuzzy logic and clustering. Clustering methods are often undeservedly forgotten, although the implementation of their algorithms is relatively simple and can be implemented even for students. In the research part of the study the modelling capabilities in data mining studies, clustering algorithms and real examples are demonstrated.
Subjects
  • clustering

  • data analysis

  • modelling

  • simulation

  • SPSS

  • SPSS Modeler

  • learning

File(s)
 THE POSSIBILITIES OF CLUSTERING LEARNING METHODS IN STUDENT EDUCATION.pdf (303.69 KB)
Scopus© citations
0
Acquisition Date
Jan 12, 2024
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