Smart online courses using computational intelligence

Abstract

Computer network security has become an important issue in recent decades, the government and several international organizations have invested in professional education and training for computer network security. In addition, with the increasing incidence of computer network security crimes, the government and several organizations have taken precautions by providing training to students about computer network security. Some parties develop learning models that are suitable for students and find appropriate learning methods to produce professionals in the field of computer network security that is more effective. The purpose of this study is to design a framework-based Learning system in the form of an Adaptive Online Open Course in Computer System Security Subjects for Information Technology (IT) students. The benefits of this framework are to enhance students' skills and abilities in industrialbased computer network security, startup companies and the ability to complete CTF competitions in IT network security. The framework designed is Adaptive in which students learn according to the interests and topics of Computer Network Security. Interest-based on students in completing the pretest per topic. Testing in this study is testing the impact and improvement of students' learning abilities and skills on Computer Security and Security System Competence testing in a small group consisting of 20 students by seeing the success of completing 3 CTF Topics with each topic totaling 100 computer network security problems in the CTF competition, the average validation result was 83.01% and the CTF exam passing rate was 93%.