A Particle Swarm Optimization Approach to Composing Serial Test Sheets for Multiple Assessment Criteria
Journal of Educational Technology & Society Volume 9, Number 3, ISSN 1176-3647 e-ISSN 1176-3647
To accurately analyze the problems of students in learning, the composed test sheets must meet multiple assessment criteria, such as the ratio of relevant concepts to be evaluated, the average discrimination degree, difficulty degree and estimated testing time. Furthermore, to precisely evaluate the improvement of student's learning performance during a period of time, a series of relevant test sheets need to be composed. In this paper, a particle swarm optimization-based approach is proposed to improve the efficiency of composing near optimal serial test sheets from very large item banks to meet multiple assessment criteria. From the experimental results, we conclude that our novel approach is desirable in composing near optimal serial test sheets from large item banks and hence can support the need of evaluating student learning status. (Contains 4 tables and 6 figures.)
Yin, P.Y., Chang, K.C., Hwang, G.J., Hwang, G.H. & Chan, Y. (2006). A Particle Swarm Optimization Approach to Composing Serial Test Sheets for Multiple Assessment Criteria. Journal of Educational Technology & Society, 9(3), 3-15.
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A Test Sheet Optimization Approach to Supporting Web-based Learning Diagnosis Using Group Testing Methods
Chu-Fu Wang & Chih-Lung Lin, National Pingtung University, Department of Computer Science, Pingtung, Taiwan; Gwo-Jen Hwang, National Taiwan University of Science and Technology, Graduate Institute of Digital Learning and Education, Taipei City, Taiwan; Sheng-Pin Kung, National Pingtung University, Department of Computer Science, Pingtung, Taiwan; Shin-Feng Chen, National Pingtung University, Department of Education, Pingtung, Taiwan
International Journal of Online Pedagogy and Course Design Vol. 7, No. 4 (October 2017) pp. 1–23
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