Abstract
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.
Highlights
Data mining is a widely spread approach for analyzing large data repositories to extract necessary or useful information
According to the literature researched in the previous stage, the activities shown in Figure 1 are recognized as some of the most important ones in educational data mining using cluster analysis and decision tree technique
The educational data mining analysis, conducted in this research, resulted with one model by cluster analysis showing groups of students according to their behavior in the elearning system and three models of decision tree made according to previously conducted cluster analysis
Summary
Data mining is a widely spread approach for analyzing large data repositories to extract necessary or useful information. The goal of data mining application is to extract hidden data patterns and to detect relationships between parameters in a vast amount of data. The exploration of data in education using data mining techniques is commonly known as educational data mining.[1] Different educational data are stored in large databases. This is especially true for online programs, for the support of teaching processes and in which student learning behaviors can be recorded and stored. Many educational institutions evaluate the performance of their students based on final grades which depend on a course structure assessment and learning objectives to achieve an effective and consistent learning process.[3]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering Business Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
