COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, cilt.18, sa.2, ss.298-305, 2010 (SCI-Expanded)
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%. (C) 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