In this application, four contributions are provided to overcome test design challenges forthe student assessment. First, a tool is developed to generate a synthetic questionpool. Second, an objective function is designed based on the considered attributes.Third, the popular swarm and evolutionary optimization methods, namely particle swarm optimization, genetic algorithm, artificial bee colony, differential search algorithm are comparatively studied with novel methodologies applied to them. Finally,as the state of the art methods, artificial bee colony, and differential search algorithm are further modified to improve the solution of the test design.
Note: QuestionPool.mat data set is included in the file.
This is the source codes of the paper : Aktaş, M., Yetgin, Z., Kılıç, F., & Sünbül, Ö. (2022). Automated test design using swarm and evolutionary intelligence algorithms. Expert Systems, 39(4), e12918. ,https://doi.org/10.1111/exsy.12918
引用格式
Aktaş, Muhammet, et al. “Automated Test Design Using Swarm and Evolutionary Intelligence Algorithms.” Expert Systems, vol. 39, no. 4, Wiley, Dec. 2021, doi:10.1111/exsy.12918.
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