Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

Researching of Intelligence Test Paper Generation Software based on Improved Genetic Algorithm in Java Program Design Teaching

Authors
Qiufang Ma, Hao Pan
Corresponding Author
Qiufang Ma
Available Online May 2017.
DOI
10.2991/icmeit-17.2017.43How to use a DOI?
Keywords
java program design, genetic algorithm, intelligent test paper generation
Abstract

Editing test papers is a very heavy mental labor. Aiming to improve the teaching effect of Java Program Design and realize the separation of teaching and test, the intelligent test paper generation software based on improved genetic algorithm is designed. The software provides three generating methods based on guaranteeing the reasonable distribution of knowledge points. The teaching practice results demonstrate that the application of the software can improve teaching quality effectively, achieve standardization of test and promote the development of teachers.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
Series
Advances in Computer Science Research
Publication Date
May 2017
ISBN
10.2991/icmeit-17.2017.43
ISSN
2352-538X
DOI
10.2991/icmeit-17.2017.43How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qiufang Ma
AU  - Hao Pan
PY  - 2017/05
DA  - 2017/05
TI  - Researching of Intelligence Test Paper Generation Software based on Improved Genetic Algorithm in Java Program Design Teaching
BT  - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
PB  - Atlantis Press
SP  - 232
EP  - 235
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-17.2017.43
DO  - 10.2991/icmeit-17.2017.43
ID  - Ma2017/05
ER  -