Research On Online Learning Process Optimization Based On Personalized Recommendation

With the popularity of the internet,it is more and more convenient to obtain network learning resources.People can learn knowledge anytime and anywhere without the limitation of time and space.As a new way of education,online learning is becoming more and more popular among learners because of its rich resources,convenient access,economic applicability and other characteristics.Some enterprises and universities begin to tap high-quality talents from online learning platform.However,most online learning platforms can only provide simple keyword search and popular recommendation functions,which can not completely solve the problems of information overload and information confusion caused by the accumulation of massive learning resources.In addition,due to the lack of humanistic care and professional guidance of teachers in traditional face-to-face education,online learning has higher requirements on learners' self-consciousness and self-control in the learning process.There are relatively few learners who can reasonably arrange their own learning process,and the effect of online learning is poor.In view of the current situation of online learning,this paper analyzes the optimization of learning process.Based on cognitive diagnosis,personalized recommendation and other theoretical knowledge,aiming at optimizing learning process,supported by Hebei Engineering Research Center Project "Hebei intelligent education big data" Engineering Research Center project,and taking database application course as empirical background,this paper studies online learning process optimization method based on personalized recommendation.First of all,it analyzes the problems and reasons in the process of online learning,and according to the reasons and theoretical knowledge of the problems,it puts forward an online learning process optimization method based on cognitive diagnosis and personalized recommendation;Then,according to the steps of cognitive diagnosis,the cognitive attributes and hierarchical relationship are determined.Combined with the relationship between learners,test questions and cognitive attributes,the test results are analyzed by using rstudio to diagnose the mastery mode of learners' cognitive attributes;Then,it constructed learner model,learning resource model and knowledge structure chart,selected collaborative filtering algorithm to recommend learning resources suitable for learners,so as to help learners complete their learning objectives in the shortest time and efficiently,further solve the cognitive overload,learning confusion and other problems in the process of online learning,and improve learners' satisfaction;Finally,through comparative experiments,from the four aspects of recommendation accuracy,learning time,test results,and learner satisfaction,it is proved that it is feasible and effective to use the improved personalized recommendation technology of online learning resources to optimize the online learning process of learners,and the effect is obvious,which further proves that the online learning process optimization method based on Personalized Recommendation proposed in this paper can be effectively solved There are some problems in the process of online learning,which can be used for reference to improve the efficiency and satisfaction of learners.