Representing examination question knowledge into Genetic Algorithm

• Published in: IEEE Global Engineering Education Conference pp. 900 - 904
• Main Authors: Teo, Noor Hasimah Ibrahim, Abu Bakar, Nordin, Abd Rashid, Mohamad Rezduan
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.04.2014
• Subjects: Automotive components; Biological cells; cognitive knowledge; Conferences; Design engineering; examination question; Fitness; Generators; Genetic Algorithm; Genetic algorithms; Instructors; knowledge extraction; Mathematical analysis; Sociology; Statistics; Taxonomy
• ISSN: 2165-9559; 2165-9567
• DOI: 10.1109/EDUCON.2014.6826203

Examination is a medium of knowing the IQ of a person and how far is the understanding of certain subjects. Normally, the questions are prepared by course instructor in sets and become a burden if the subject is new to them as they needs to prepare it in a given time. This paper describes a method of auto generating a new set of final exam questions. The objectives of this paper are: to optimize selection of final examination question based on the Cognitive Level of Blooms Taxonomy; to design and develop a prototype of auto-generator examination question using Genetic Algorithm and to evaluate performance of this tool. There are many types of questions in an examination; but this system chooses to analyze the structured question only. The newly populated examination questions are based on the fittest value of the fitness function calculated. This technique can be upgraded and be used by other type of question too.