Open AccessEffectiveness analysis of machine learning in education big data
Author(s) -
Zhou Ya,
Zhuoqing Song
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012105
Subject(s) - big data , computer science , field (mathematics) , space (punctuation) , data science , rationality , artificial intelligence , value (mathematics) , machine learning , data mining , political science , mathematics , pure mathematics , law , operating system
In the education big data environment, the online data and information of the current education industry learning resources supply become complex and diverse. Different scenarios and different analysis environments face different learners. Combined with the current education field in China, prediction, evaluation and analysis play an important application value and broad space for education and teaching. Machine learning technology has strong learning ability. Breaking the limitation of time and space, deeply analyzing the rationality of data relationship and obtaining the effectiveness evaluation are the effective means to explore this field. As well as a way to summarize the general rules and trends of using machine learning in education big data and educational data mining.