Advanced SearchSearch Tips
Improving Lecture Quality using SOFM neural network and C4.5
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Improving Lecture Quality using SOFM neural network and C4.5
Lee, Jang-hee;
  PDF(new window)
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.
C4.5;Education Service;Lecture Quality;Satisfaction;SOFM;
 Cited by
H. L. Park, "A study on the improvement of a lecture evaluation tool in higher education -A case of improvement of a lecture evaluation questionnaire in "A" university-," Journal of the Korea Academia-Industrial cooperation Society, vol. 13, no. 11, pp. 5033-5043, 2012.

P. D. Cohen, "Effectiveness of student rating feedback for improving college instruction: A meta-analysis of findings," Research in Higher Education, vol. 13, no. 4, pp. 321-341, 1980.

H. A. Andrews, Teachers can be Fired! The Quest for Quality. Peru, IL: Catfeet Press, 1995.

K. D. Peterson, Teacher Evaluation: A Comprehensive Guide to New Directions and Practices. Oaks, CA: Corwin Press, 1995.

K. H. Lee, "A study on validity and reliability of students' evaluation," Journal of Korean Data and Information Science Society, vol. 21, no. 1, pp. 87-98, 2010.

K. H. Choi and S. J. Lee, "A suggestion on instruction service quality assessment tool," Applied Statistics Research, vol. 18, no. 2, pp. 487-497, 2005.

J. T. Kim and J. M. Lee, "A study on reliability of lecture evaluation by students," Journal of Korean Data and Information Science Society, vol. 15, no. 1, pp. 183-191, 2004.

C. H. Ryu and J. H. Lee, "A study on student factors associated with the student evaluation of teaching at universities," Korean Management Review, vol. 32, no. 3, pp. 789-807, 2003.

T. Kohonen, Self-Organization and Associative Memory, 3rd ed. Berlin: Springer-Verlag, 1989.

J. R. Quinlan, C4.5: Programs for Machine Learning. San Francisco, CA: Morgan Kaufmann Publishers, 1993.