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
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.
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Received: 2021-01-08 Revised: 2021-03-08 Accepted: 2021-04-07 Available Online: 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.
