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http://dx.doi.org/10.14702/JPEE.2014.071

Improving Lecture Quality using SOFM neural network and C4.5  

Lee, Jang-hee (School of Industrial Management, KOREATECH)
Publication Information
Journal of Practical Engineering Education / v.6, no.2, 2014 , pp. 71-76 More about this Journal
Abstract
Improving lecture quality is very necessary for the service quality of education in universities, enterprises and education institutes. The student lecture evaluation survey data is a good tool for measuring lecture quality and have been often analyzed by simple statistical methods. This study presents an intelligent lecture quality improvement method that can improve student's overall satisfaction and performance by analyzing student lecture evaluation survey data. The method uses SOFM (Self-Organizing Feature Map) neural network and C4.5 to find the patterns in student's satisfaction and performance more correctly and then decide what to change in the lecture for the improvement of student's satisfaction and performance. We apply the proposed method to an enterprise lecture in Korea. We can find that it can improve the quality of an enterprise lecture by changing total lecture time, lecture material and organization of lecture schedule to be necessary improvements.
Keywords
C4.5; Education Service; Lecture Quality; Satisfaction; SOFM;
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