The Classification Model of Learners Based on Diagnostic Assessment Results in E-learning With Machine Learning

• Published in: 2022 1st International Conference on Software Engineering and Information Technology (ICoSEIT) pp. 67 - 72
• Main Authors: Yel, Mesra Betty, Zarlis, Muhammad, Suwilo, Saib, Efendi, Syahril, Sihombing, Poltak
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22-11-2022
• Subjects: Classification algorithms; classification diagnostic assessment e-learning; Clustering algorithms; diagnostic assessment based on machine learning; Electronic learning; Information technology; Machine learning; Machine learning algorithms; Training
• DOI: 10.1109/ICoSEIT55604.2022.10030060

The development of technology and artificial intelligence, especially in the era of Industrial Revolution 4.0 almost covers all fields, one of which is e-learning. In its development, it is very important to determine the factors to produce the quality of e-learning. Machine learning can help to find various solutions in the real world, especially to solve problems for which a specific algorithm has not been found. The implementation of e-learning is often ineffective and not on target which has an impact on learning achievement that is not achieved, this is due to several things namely the learning model is applied in general, the learning materials and weights are applied equally to all users. Seeing these problems, it is necessary to have a model to classify students according to their abilities, talents, and interests before starting learning to achieve their goals to be achieved. This paper aims to create a machine learning approach model to determine the level of ability and needs of students before starting learning which can reduce disparities between students and follow up learning materials. With the machine learning based on learning model, e-learning can provide teaching materials according to the abilities, and interests of students, sustainably and improve the quality of students.