Abstract

Conducting tests by extracting questions manually and using random methods of generating tests from question banks consumes a great deal of time and effort, The quality of the resulting tests is often inaccurate and the tests created may not exactly match the requirements that were previously formulated, This study focused on innovative ways to enhance the process of researching questions in ways that meet the extraction requirements and conditions that have been identified, This study proposes a genetic algorithm (GA) to generate multiple choice tests based on the difficulty levels of the questions and the extracted ratings, Experiments and analyzes with the proposed mutation operator demonstrated the success of the (GA) method with a very high percentage, An electronic system was designed to select and evaluate questions and their level of difficulty based on a genetic algorithm.

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