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Title:
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EDUCATIONAL DATA MINING: ANALYZING SCIENCE PROJECT COURSES IN ORDER TO IMPROVE EDUCATIONAL PROCESSES |
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Author(s):
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Konrad Michalski , Rafal Michalski |
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ISBN:
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972-8939-03-5 |
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Editors:
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Pedro Isaías, Piet Kommers and Maggie McPherson |
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Year:
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2005 |
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Edition:
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Single |
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Keywords:
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Distance education, university, data mining, analysis. |
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Type:
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Short Paper |
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First Page:
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422 |
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Last Page:
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427 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The paper investigates and researches approaches to analyzing the student educational information and concentrates on science 400 level project based courses going back twenty five years. 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. |
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