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A genetic algorithm for generating test from a question bank
Author(s) -
Yildirim Mehmet
Publication year - 2010
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.20260
Subject(s) - crossover , usable , mutation , operator (biology) , genetic algorithm , test (biology) , computer science , algorithm , integer (computer science) , artificial intelligence , machine learning , programming language , genetics , paleontology , repressor , biology , world wide web , transcription factor , gene
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