Prediction of e-Learning Efficiency by Neural Networks

1. John, M. Economic Forecasting Challenges and Neural Network Solutions. Computer Science Dept., Oregon Graduate Institut, USA, 1995.Search in Google Scholar

2. Hou, Zai-En, Fu-Jian Duan. The Neural Network Method of Economy Forecasting. World Congress on Software Engineering, IEEE, 2009.10.1109/WCSE.2009.397Search in Google Scholar

3. Leonardo, M. S., R. Ballini. Design a Neural Network for Time Series Financial Forecasting: Accuracy and Robustness Analisys. Instituto de Economia, Universidade Estadual de Campinas, Sao Paulo-Brasil, 2008.Search in Google Scholar

4. Lykourentzou, I., I. Giannoukos, G. Mpardis, V. Nikolopoulos, V. Loumos. Early and Dynamic Student Achievement Prediction in e-Learning Courses Using Neural Networks. DOI: 10.1002/asi.20970, 2008.10.1002/asi.20970Search in Google Scholar

5. Lykourentzou, I., I. Giannoukos V. Nikolopoulos,, G. Mpardis, V. Loumos. Dropout Prediction in e-Learning Courses through the Combination of Machine Learning Techniques. School of Electrical and Computer Engineering, National Technical University of Athens, Zographou Campus, 15773 Athens, Greece, 2009.10.1016/j.compedu.2009.05.010Search in Google Scholar

6. Kasuba, A. EXPERT. Simplified Fuzzy ARTMAPT. Miller Freeman, Inc., 1993.Search in Google Scholar

7. Baker, B. D., C. E. Richards. A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending. 1999.10.1016/S0272-7757(99)00003-5Search in Google Scholar

8. Zhong, He De, Liu Jing Nan, Zhang Su He. Evaluation of Academic Degrees and Graduate Education Based on Neural Network. - Journal of Chongqing University (Natural Science Edition), 2003.Search in Google Scholar

9. Kaplan, R., D. Norton. The Balanced Scorecard: Translating Strategy into Action. 2006.Search in Google Scholar

10. Johnson, K. J. Boosting Performance and Accountability with the BSC. Texas Education Agency, 2003.Search in Google Scholar

11. Lilian, C. Y.-C. Which Balanced Scorecard to Use. St. Thomas University, 2007.Search in Google Scholar

12. Purdue University, SSTS: Strategic Plan - Balanced Scorecard. 2009.Search in Google Scholar

13. Cardoso, M. J. T. P. N. E. A Balanced Scorecard Approach for Strategy-and Quality-Driven Universities. 2005.Search in Google Scholar

14. Nicola, B. R. K. R. S. SPSS for Psychologists. Published by Palgrave Macmillan, Australia, 2006.Search in Google Scholar

15. Vundev. Records on Applied Statistics, Vol. 2, 2003.Search in Google Scholar

16. Edward, J. J. A User's Guide to Principal Components, 2004.Search in Google Scholar

17. Suikova , S. Т. I. Statistical Study. Publishing House “Luren”, 2000.Search in Google Scholar

18. S. M. Cross-Validatory Choice and Assessment of Statistical Predictions. 1974.Search in Google Scholar

19. Cun, Yan Le, J. Denker, S. Solla. Optimal Brain Damage. Advances in Neural Information Processing Systems, 1990.Search in Google Scholar

20. Cybenko, G. Approximation by Superposition of a Sigmodial Function. 1986.Search in Google Scholar

21. Funahashi, K.-I. On the Approximate Realization of Continuous Mappings by Neural Networks. 1989.10.1016/0893-6080(89)90003-8Search in Google Scholar

22. Hartman, K., Kowalski. Layered Neural Networks with Gaussian Hidden Units as Universal Approximations. 1990.10.1162/neco.1990.2.2.210Search in Google Scholar

23. Haykin, S. Neural Networks: A Comprehensive Foundation. 1994.Search in Google Scholar

24. Kuruglov, V. V., M. I. Dli, R. Golunov. Fuzzy Logic and Artificial Neural Networks. 2001.Search in Google Scholar