International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Yung-Fa Huang1, Hsing-Chung Chen2*, Pi-Ling Yen3

1 Deptartment of Information Management, Chaoyang University of Technology, Taichung, Taiwan
2 Deptartment of Computer Science and Information Engineering, Asia University, Taichung, Taiwan
3 Deptartment of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, Taiwan


 

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ABSTRACT


In this paper, we propose an improved Grey relational analysis (GRA) model to enhance the strategy of tests items selection. In general, the strategy of tests items selection is based on the item response theory (IRT) to select test items by the measuring information of target test items. Five ability levels are used to set out the target information for items selection. Simulation results show that the proposed improved GRA model with scaling factor by 1.5, under the number of items by 10, 15, 20, 25, and 30, performs better than both the average target information (ATI) and random methods in mean square error (MSE). Furthermore, the improved GRA model while the number of items is 20 could largely achieve lower MSE of test information error (TIE) by 0.8 comparing to the 2.6 and 4.2 of ATI and random methods, respectively.


Keywords: Grey system theory, Grey relational analysis, Item response theory, Target information, Item selection strategy.


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REFERENCES


  1. Crocker, L., Algina, J. 1986. Introduction to classical and modern test theory. Holt, Rinehart and Winston. Florida. U.S.A.

  2. Deng, J. 1992. Grey system theory tutorial. Huazhong University of Science and Technology Press. Wuhan. China.

  3. Deng, J. 1996. Basic method of grey system. Huazhong University of Science and Technology Press. Wuhan. China.

  4. Fives, H., Barnes, N. 2016. Informed and uninformed naïve assessment constructors’ strategies for item selection, Journal of Teacher Education. https://doi.org/10.1177/0022487116668019.

  5. He, R., Du, L., Zhuang, Q. 1998. Improved grey prediction computerized suitability test selection items. Proceeding of Seventh International Computer-aided Teaching Symposium, 393–400.

  6. Hirose, H., Aizawa, Y. 2014. Automatically growing dually adaptive online IRT testing, Proceeding of International Conference of Teaching, Assessment and Learning (TALE), 528–533.

  7. Lord, F.M. 1980. Applications of item response theory to practical testing problems. Routledge. Taylor & Francis. New York. U.S.

  8. Muddineni, V.P., Bonala, A.K., Sandepudi, S.R. 2020. Grey relational analysis based objective function optimization for predictive torque control of induction machine. Proceeding of 2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (PESGRE2020).

  9. Sun, G., Chen, Y., Lai, Y., Xie, K., Chen, X. 1999. Using greedy algorithms as a profitable item selection strategy. Proceeding of National Computer Conference. Tamkang University. Taipei, Taiwan, 379–386.

  10. Wen, K.-L., Wu, J.H. 1996. On distinguishing coefficient & relational grade. The Journal of Grey System, 8, 11–18.

  11. Wong, C.C., Lai, H.R. 2000. A new grey relational measurement. The Journal of Grey System, 12, 341–346.

  12. Younas, M., Jaffery, S.H.I., Khan, M., Khan, M.A., Ahmad, R., Mubashar, A., Ali, L. 2019. Multi-objective optimization for sustainable turning Ti6Al4V alloy using grey relational analysis (GRA) based on analytic hierarchy process (AHP). The International Journal of Advanced Manufacturing Technology, 105, 1175–1188.

  13. Yu, M. 1993. Computerized adaptability test. Study Information, 10, 5–9.

  14. Yuan, C., Zhang, Y., Xu, N., Xu, J. 2017. Grey relational analysis on the relation between China's GDP and defense expenditure, Proceeding of 2017 IEEE International Conference on Grey Systems and Intelligent Services (GSIS).


ARTICLE INFORMATION


Received: 2021-01-08
Revised: 2021-03-08
Accepted: 2021-04-07
Publication Date: 2021-09-01


Cite this article:

Huang, Y.-F., Chen, H.-C., Yen, P.-L. 2021. Performance of computer examination items selection based on grey relational analysis. International Journal of Applied Science and Engineering, 18, 2021009. https://doi.org/10.6703/IJASE.202109_18(5).007

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


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