The Analysis And Research Of Online Learning Behavior Based On Data Mining Technology

The development of internet technology has also fostered the development of education,and brings people into the era of "Internet+education".Online learning,online work,online discussion and other diverse learning methods through network have also been accepted by more and more people.Online learning is generally refers to the online learning behavior through the online learning platform,which breaks the limitations of time and space in traditional teaching methods,and gives learners a great deal of convenience and freedom,but at the same time it still has many problems.Most of the learning platforms are simply pushed into learning content,without considering the differences between students.As for learners,there are too many learning resources with complex structure to extract what they really need.Therefore it is necessary to analyze the online learning behavior and apply it to the online learning system for the learners to have some guidance and promotion of online learning.This paper do some research and improvement to the algorithms of association rules and sequence pattern mining,and on this basis,the improved algorithms are used to collect and analyze the data of learning behavior.Finally,the data mining technology is applied to the personalized learning system,optimize the mechanism of online learning and the user's learning experience.The main work is as followed:1.Introduced the domestic and foreign research status of online learning behavior analysis and data mining technology,and expounds the research background of this paper,then discusses the practical use and significance of learning behavior mining.2.Making a deep understanding of the concepts and characteristics of online learning behavior and the process and algorithms of data mining technology,and studing how to construct efficient and reliable online learning behavior analysis methods.3.The related methods of learning behavior mining are studied.The association rules and sequential pattern mining are analyzed in detail,and the Apriori algorithm and Apriori All algorithm are optimized.The performance of the two algorithms are compared and tested,and the results show that the improved algorithm has better performance.4.The learning behavior is analyzed and the learning behavior mining model is constructed on this basis.The paper uses the improved algorithms to excavate the learning behavior data,including the preprocessing and conversion of the data in the database,to dig the learning sequence pattern and the relationship between the learning behavior and the learning effect respectively.Finally,the mining result is explained and evaluated.5.Constructs a personalized learning system based on learning behavior mining,and implements each module,including designing and developing the learning platform,collecting and preprocessing the learning behavior data,and personalizing the learning resources according to the result of data mining recommendations and so on.6.Finally,the personalized learning system is tested,evaluated and analyzed to verify its feasibility.