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Educational Data Mining and Reporting: Analyzing Student Data In Order To Improve Educational Processes
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, Athabasca University, Canada ; , MICKORA, Poland

EdMedia + Innovate Learning, in Lugano, Switzerland ISBN 978-1-880094-53-2 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC

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Abstract

Abstract: The paper investigates and researches approaches to analyzing the student educational information. The dynamic data mining techniques are used according to the needs of the analyst in order to improve the educational processes. The student data mining process allows to have a better perspective on the student progress throughout the educational processes, and at the same time to analyze the information related to the specifics of the programs, courses, and course assignments. This innovative approach allows the decision making process to use the what-if scenario when analyzing the student data, and other education related information in order to improve educational processes. The data related to the students' progress is retrieved from the students' records, imported into the data mining system, analyzed, and exported back. The educational data mining allows identifying and locating details about educational processes that need improvements, or those that perform very well and could be used as good examples.

Citation

Michalski, K. & Michalski, R. (2004). Educational Data Mining and Reporting: Analyzing Student Data In Order To Improve Educational Processes. In L. Cantoni & C. McLoughlin (Eds.), Proceedings of ED-MEDIA 2004--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 1088-1094). Lugano, Switzerland: Association for the Advancement of Computing in Education (AACE). Retrieved March 24, 2023 from .

© 2004 Association for the Advancement of Computing in Education (AACE)

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References

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