Study On The Application Of Learning Analysis Technology In University Education

The rapid development of science and technology has driven the rapid development of education informatization.Imperceptibly,people’s learning way has changed from a single traditional classroom learning mode to a diversified learning way.The arrival of a variety of flexible teaching methods is a large number of educational data,which includes both traditional performance data and other forms of behavioral data,as well as a variety of text data,and so on.In the past period of time,due to technical and other reasons,these educational data have been neglected by people.However,in the process of scientific and technological advancement,these data have gradually been valued by scholars.In this process,the learning and analysis technique is born and is gradually becoming a research hotspot in the field of education.The purpose of this study is to explore and analyze education data,so that these data can serve learners,professors and managers.Its significance in education and teaching is evident.Learning and analysis technology originated in foreign countries,and domestic research on it began to be gradually studied later than in 2012.However,at present,researches in the field of learning and analysis technology are mostly theoretical and there are few applied researches.Especially for some online education institutions,the application of learning analysis technology in primary and secondary schools and universities is relatively scarce.After studying and researching the theoretical knowledge and application examples of learning analysis technology,this study makes three experiments which uses the decision tree algorithm,the AdaBoost algorithm and the TOPSIS evaluation method to design the three aspects of the learning analysis technology in personalized learning,learning prediction intervention and learning resource allocation,combined with the present situation of college education.Experiment one is to study the effects of personalization factors on college students’ English CET-6 and college English application proficiency test(spoken language)tests through differences,correlation analysis,and decision tree methods.It was proposed for students of different colleges and genders to provide personalized learning strategies.In the experiment two uses the adaboost algorithm to construct a predictive intervention model,which predicts some students’ learning situation of there major subjects in the four years.And provides personalized remedial advice for students who are predicted to be in a "dangerous" state.In experiment three,the study of free normal students was analyzed.It was found that the performance of the class was not superior to that of the non-free normal students.Therefore,on the basis of the TOPSIS evaluation method,the training scheme was evaluated quantitatively.The study of the above three experiments on the one hand does provide some valuable suggestions and models for learning and analysis for specific institutions.On the other hand,it hopes to enrich the research on applications in the field of domestic learning analysis and provide some new ideas for other scholars.