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Educational data mining using cluster analysis and decision tree technique: A case study (CROSBI ID 275668)

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Križanić, Snježana Educational data mining using cluster analysis and decision tree technique: A case study // International journal of engineering business management, 12 (2020), 1-9. doi: 10.1177/1847979020908675

Podaci o odgovornosti

Križanić, Snježana

engleski

Educational data mining using cluster analysis and decision tree technique: A case study

Data mining refers to the application of data analysis techniques with the aim of extracting hidden knowledge from data by performing the tasks of pattern recognition and predictive modeling. This article describes the application of data mining techniques on educational data of a higher education institution in Croatia. Data used for the analysis are event logs downloaded from an e-learning environment of a real e- course. Data mining techniques applied for the research are cluster analysis and decision tree. The cluster analysis was performed by organizing collections of patterns into groups based on student behavior similarity in using course materials. Decision tree was the method of interest for generating a representation of decision-making that allowed defining classes of objects for the purpose of deeper analysis about how students learned.

Educational data mining, cluster analysis, decision trees, case study, log file

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Podaci o izdanju

12

2020.

1-9

objavljeno

1847-9790

10.1177/1847979020908675

Povezanost rada

Informacijske i komunikacijske znanosti

Poveznice
Indeksiranost