Design and Application of the Network Distance Teaching System

Article Preview

Abstract:

Computer network generate a spatial and temporal separation in teaching activities, the new feature of the online teaching also make it possible to improve students' learning efficiency by using of the theory of interactive activities and appropriate teaching strategies. This paper mainly discuss the problems exist in distance teaching system based on the Internet, and design an prototype model for distance teaching which could achieve a unified and efficient management of curriculums, teachers, students and teaching resource according to the specific requirement of school.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

1017-1020

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Carreras X , Marquez L. Boosting Trees for Anti-Spam Email Filtering[C]. In : Proceedings of Euro Conference Recent Advances in NLP (RANLP-2001). 2001: 58-64.

Google Scholar

[2] Cohen W. Fast Effective Rule Induction[C]. In Machine Learing: Proceedings of the Twelfth International Conference , Lake Taho , California , Mongan Kanfmann , 1995: 115-123.

Google Scholar

[3] Cohen W. Learning Rules that Classify email[C]. In Proceedings of the AAAI spring symposium of Machine Learning in Information Access , Palo Alto, California , 1996: 18-25.

Google Scholar

[4] Drucker H, Wu D, Vapnik V N. Support Vector Machines for Spam Categorization, [J]. IEEE Transactions on Neural Networks. 1999 , 20(5): 1048-1054.

DOI: 10.1109/72.788645

Google Scholar

[5] Nicholas T. Using AdaBoost and Decision Stumps to Identify Spam E-mail [EB] . Stanford University Course Project (Spring 2002/2003) Report, http: /nlp. stanford. Edu/courses/ cs224n/2003/fp/tyronen/report. pdf.

Google Scholar

[6] Androutsopoulos I, Paliouras G , Michelakis E. Learning to Filter Unsolicited Commercial E-Mail [EB] . Technical report 2004/2 , NCSR"Demokritos", (2004).

Google Scholar

[7] Pawlak Z. Rough set [J]. Inter Journal of Computer and Information Sciences, 1982, 11: 341-356.

Google Scholar