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- W1965511704 abstract "The purpose of this study is to provide academicians with efficient means of generating tests with multiple-choice questions from a question bank. Genetic algorithm (GA) is used to optimize predefined criteria for selecting questions from the question bank. GA is a very useful optimization algorithm because of its versatility. However, crossover and mutation operator of standard GA cannot be directly usable for generating test, since integer-coded individuals have to be used and these operators produce duplicated genoms on individuals. In this study, a mutation operation is proposed for preventing the duplications on crossovered individuals. The experiments and analysis show that GA with proposed mutation operator is successful as approximately 100%. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 298–305, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20260" @default.
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- W1965511704 date "2009-01-01" @default.
- W1965511704 modified "2023-10-02" @default.
- W1965511704 title "A genetic algorithm for generating test from a question bank" @default.
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- W1965511704 doi "https://doi.org/10.1002/cae.20260" @default.
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