Design of Online Learning Early Warning Model Based on Artificial Intelligence

Abstract

Students have produced a large number of learning logs and a large number of educational data through online learning. In order to extract useful information from these massive information, support teachers’ teaching activities, improve teaching quality, provide learners with personalized learning support, and teach students according to their aptitude, educational big data analysis has attracted extensive attention of educators. Under the impact of informatization, education and information technology are deeply integrated, and network education is in the ascendant. At the same time, the theories and methods of artificial intelligence are gradually applied to the field of education. Learning analysis, data mining, and other analysis methods provide effective analysis methods for online learning process and learning effect. This paper studies the design of online learning early warning model based on artificial intelligence. When the system is implemented, based on the existing evaluation index system, the online learning early warning model of analytic hierarchy process is introduced to give different evaluation indexes unequal weights to ensure the fairness of evaluation. On the basis of understanding the artificial intelligence algorithm, the corresponding detection indicators should also be selected according to the objectives of the online learning early warning model and the needs of the actual work of network operation and maintenance. Then, follow the corresponding data flow of artificial intelligence technology and analyze data preprocessing, feature selection, and model training.