Construction And Analysis Of Learner Learning Behavior Model Based On Online Learning Environment

With the rapid development of online education,online learning has become one of the mainstream ways of learning,and has been widely recognized by the education community.The all new way of education and learning has made the concept of educational informatization a new development,and the transformation and innovation of education will be driven again.Of course,at the same time,the rapid development of online education has encountered different levels of challenges,such as higher dropout rates for learners,low completion rate and loss of users.In order to find out the reason for this phenomenon,based on the online learning environment,researchers use the Network teaching platform to generate a large amount of learning behavior data,and analyze the learner's learning behavior data to solve various complex problems faced by online learning.Through the analysis of learner's learning behavior data,it provides effective supervision and intervention learning process for teachers and Network teaching platform administrators,develops more reasonable learning plans for online learners,and provides more effective support for online learners and service.Firstly,on the basis of summarizing the research status of online learning behavior at home and abroad and the research fields related to learning behavior analysis,this paper explains the definition of online learning behavior and the related concepts of classification model,data analysis algorithm and data mining.Based on the relevant models of learning behavior analysis,combined with Yunnan Normal University's Er'ya Network teaching platform,the principles and ideas for constructing learners' online learning behavior analysis models are proposed.The learning behaviors in this paper are mainly divided into explicit learning behaviors and implicit learning behaviors,and the implicit learning behavior dimensions and explicit learning behavior dimensions are divided,and the learning behavior analysis model is constructed.Secondly,according to the constructed online learning behavior analysis model,the implicit learning behavior dimension is based on the questionnaire,and the simple results of Excel are used to obtain the corresponding results.The explicit learning behavior collected the learning behavior data of the learner's management background on the Yunnan Normal University's Er'ya Network teaching platform.Using the data analysis software Weka3.8.3,the K-means algorithm was used to cluster and analyze the learner's explicit learning behavior.Then use SPSS22.0 to analyze the explicit learning behavior and implicit learning behavior,and analyze the correlation value between the two.Thirdly,the research results of the learning behavior are further analyzed to convert the degree of learning behavior.The analysis of the correlation between each implicit learning behavior dimension and explicit learning behavior is analyzed,and the application effect and related application enlightenment of Er'ya Network teaching platform learning behavior analysis are given.It not only provides learners with self-learning evaluation and intervention in the online learning environment,but also provides strong evidence for the teacher's teaching decision-making and optimization in the online learning environment,and provides effective support for the monitoring and management of platform managers.The effectiveness of the learner's learning behavior analysis model is verified.If the model is valid,the online learning behavior can be analyzed according to the learner's learning behavior model,which provides a reference scheme for in-depth study of the learner's online learning behavior.Finally,the author makes a corresponding summary and outlook for this research,and supplements the research deficiencies.