Author(s)

Ya’ning Yan

Corresponding Author

Ya’ning Yan

Abstract

With the rise of large data in education, how to analyze a large number of data to support accurate prediction is a new topic in the era of artificial intelligence. Machine learning, as an important branch of artificial intelligence, can meet the needs of large data analysis and prediction in education. For this reason, based on a series of questions such as “why to analyze, what to analyze, why to analyze and how to apply”, the appropriateness of machine learning and wisdom education is discussed through the analysis of the object, process and specific methods of machine learning. Combining with the analysis and summary of the case studies on the application of machine learning education based on real data abroad in recent years, it is found that the current application of machine learning education mainly focuses on six aspects: student modeling, student behavior modeling, prediction of learning behavior, early warning of the risk of dropout, learning support and evaluation, and resource recommendation.

Keywords

Machine learning; Intelligent education; Artificial intelligence; Educational big data; Educational innovation