Constructing multiple choice tests from question banks using swarm based optimization

Abstract

In this thesis, a popular swarm-based optimization is proposed to construct numerous multiple-choice tests from different question banks which can satisfy different criteria which is called Artificial Bees Colony (ABC) algorithm. This is also a metaheuristic algorithm which is used frequently in solving single-objective optimization problems. ABC algorithm allows users to generate many tests having difficulty levels approximate the predefined difficulty level in one attempt. The experimental results of the research show that this method has the ability to extract multiple tests at the same time but still satisfies other criteria such as the difficulty level, extracting time, standard deviation and the population size which are used to display the effectiveness of the method towards the problem.