The Research of Examination Paper Generation Based on Index System Metrics and Multi-Objective Strategy

Yan Li, Ji-Qiang Tang

Engineering Research Center of Mechanical Testing Technology and Equipment, Chongqing University of Technology, Chongqing, China.
Information & Education Technology Center, Chongqing University of Technology, Chongqing, China.

DOI: 10.4236/jsea.2012.58073                

Abstract

Since the examination paper generated with computer by the algorithms of random and backtracking takes on inferior quality and inefficient, and the question of generating examination paper with computer has the character of multi-ob-jective because of the index system metrics, the genetic algorithm with multi-objective strategy optimization is proposed to solve this problem. Mapping the index system to multi-objective functions and optimizing the computing with multi-objective strategy are employed in the algorithm. The genetic algorithm experiment based on the multi-objective strategy optimization shows that the result has the advantages getting tradeoff between performance and quality, and having the ability to tune the performance and quality to meet the user’s requirements.

Keywords

Generating Examination Paper with Computer; Multi-Objective Strategy; Genetic Algorithm

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	B. P. Butz, M. Duarte and S. M. Miller, “An Intelligent Tutoring System for Circuit Analysis,” IEEE Transactions on Education, Vol. 49, No. 2, 2006, pp. 216-223. doi:10.1109/TE.2006.872407
[2]	O. G. Bellmunt, D. M. Miracle, S. G. Arellano, A. Sumper and A. S. Andreu, “A Distance PLC Programming Course Employing a Remote Laboratory Based on a Flexible Manufacturing Cell,” IEEE Transactions on Education, Vol. 49, No. 2, 2006, pp. 278-284. doi:10.1109/TE.2006.873982
[3]	G. J. Hwang, B. M. T. Lin, H. H. Tseng and T. L. Lin, “On the Development of a Computer-Assisted Testing System with Genetic Test Sheet-Generating Approach,” IEEE Transactions on Systems, Man, and Cybernetics-Part C, Vol. 35, No. 4, 2005, pp. 590-594. doi:10.1109/TSMCC.2004.843184
[4]	S. C. Wang and Y. H. Liu, “Software-Reconfigurable e-Learning Platform for Power Electronics Courses,” IEEE Transactions on Industrial Electronics, Vol. 55, No. 6, 2008, pp. 2416-2424. doi:10.1109/TIE.2008.922592
[5]	H. M. Gao and Y. J. Li, “An Autogenerating Test Paper Method Based on Latent Semantic Analysis and Genetic Algorithm,” International Workshop on Intelligent Systems and Applications, Wuhan, 23-24 May 2009, pp. 1-4. doi:10.1109/IWISA.2009.5072709
[6]	P. Guo, L.-L. Liu and Q. Yao, “An Intelligent Test Sheet Composition System,” International Workshop on IT in Medicine and Education, Xiamen, 12-14 December 2008.
[7]	X.-M. Hu and J. Zhang, “An Intelligent Testing System Embedded with an Ant Colony Optimization Based Test Composition Method,” IEEE Congress on Evolutionary Computation, Trondheim, 18-21 May 2009, pp. 1414-1421.
[8]	O.-Y. Yong and H.-F. Luo, “Computer-Based Language Testing Perspectives of the Past and the Future,” Computer Science & Education, 25-28 July 2009, pp. 1764-1768.
[9]	W. Huang and Z.-H. Wang, “Design of Examination Paper Generating System from Item Bank by Using Genetic Algorithm,” Computer Science and Software Engineering, Vol. 5, 2008, pp. 1323-1325.