Design And Implementation Of Personalized Consolidation And Review System Based On Learner Behavior Data

With the rapid development of internet technology,a combination of education and information has become more closely related.Fewer Consolidation and Review Systems have appeared among large numbers of online learning systems,so it is urgent and necessary to develop the system based on learner behavior data analysis to meet the personalized needs of students.In order to develop the Consolidation and Review System,the following study was conducted.Firstly,the current situation and development trends of online learning systems at home and abroad were surveyed,and related technologies used in developing the system were expounded.Secondly,task management functions were designed for teachers,and learning curves and review questions were designed for students.The teacher could guide students to efficient review by means of distributing task in real time according to students' learning procedure.Learner behavior data could be classified and processed to form the trajectory of past learning contents so that students could review the knowledge by browsing the learning trajectory.Error-prone and difficult knowledge would be obtained by applying data analysis algorithm to learner behavior data,and then tests that matched with the error-prone and difficult knowledge would be searched from test library,afterwards tests of high coverage of knowledge would be screened out by screening algorithm,at last Review Tree made of error-prone and difficult questions would be bult.Students would make the knowledge complete by leak filling with Review Tree.Besides,ASP.NET of three-tier framework based on B/S structure was used in the system,and diversified technical support was applied to make the system stable,excellent and extensible.With the Consolidation and Review System based on learner behavior data analysis and Review Tree scientifically made of corrections,key points and difficulties,students could rapidly master the knowledge of diverse disciplines and achieve greater efficiency so as to improve the quality of review.