Design of Resource Matching Model for Intelligent Education System Based on Machine Learning

Abstract

The educational revolution brought by new technology is making a robust progress. Artificial intelligence and
intelligent education lead the innovation of education and teaching, so they have become an inevitable trend of the
educational informationizationdevelopment. With the rise of big data in education, how to analyze a large amount
of data to support accurate prediction is a new topic in the era of artificial intelligence. As an important branch of
artificial intelligence, machine learning can meet the requirements for the analysis and prediction of educational
big data. Therefore, based on a series of questions, such as “why to analyze, what to analyze, how to analyze, why
to apply”, the applicablenessof machine learning and wisdom education was discussedby analyzing the action
objects, process, specific methods, and stakeholders. Through summarizing the case studies of machine learning
education applications based on real data in recent years, it was found that the current application of machine
learning education is mainly concentrated in student modeling, student behavior modeling, learning behavior
prediction, early warning of dropout risk, learning support, as well as evaluation and resource recommendation.
Then starting from the perspectiveof crossover, technology, and teaching, some suggestions were put forward for
the educational application and innovation of machine learning based on the framework of intelligent education.