Design of Resource Matching Model for Intelligent Education System Based on Machine Learning
Yanbo Sun · 2021
The educational revolution brought by new technology is making a robust progress. Artificial intelligence andintelligent education lead the innovation of education and teaching, so they have become an inevitable trend of theeducational informationizationdevelopment. With the rise of big data in education, how to analyze a large amountof data to support accurate prediction is a new topic in the era of artificial intelligence. As an important branch ofartificial intelligence, machine learning can meet the requirements for the analysis and prediction of educationalbig data. Therefore, based on a series of questions, such as “why to analyze, what to analyze, how to analyze, whyto apply”, the applicablenessof machine learning and wisdom education was discussedby analyzing the actionobjects, process, specific methods, and stakeholders. Through summarizing the case studies of machine learningeducation applications based on real data in recent years, it was found that the current application of machinelearning education is mainly concentrated in student modeling, student behavior modeling, learning behaviorprediction, 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 forthe educational application and innovation of machine learning based on the framework of intelligent education.