Research And Application Of Online Learning Resource Recommendation System For Adaptive Learning

Under the background of digital education era,intelligent learning mode in "Internet + education" has received great attention,and adaptive learning has become the new normal of online learning.However,the rapid growth and disordered distribution of learning resources have brought challenges to online learning.How to solve such problems as learning loss,inappropriate resource recommendation and poor learning effect is of practical significance to improve the efficiency and quality of online learning.This research in learning resources recommendation system into the concept of adaptive learning,construct adaptive learning resources recommendation system and research on the application,designed to provide more suitable learning resources for learners,to promote learning resources recommended efficiency and learning effect,make online learning more effective,interactive and interesting.The main work of this study is as follows:（1）Build an adaptive recommendation model for online learning resources.Firstly,based on the literature analysis of adaptive learning and the review of the research status of learning resource recommendation system,the paper analyzes the concept and connotation of adaptive learning and learning resource recommendation system.Secondly,the learner model is designed with reference to the standard model and the knowledge model is designed based on ontology.Finally,an adaptive recommendation model of online learning resources is constructed by combining adaptive recommendation services and strategies.（2）Design an adaptive recommendation service for online learning resources.Based on the analysis of learners’ characteristics and actual learning situation,adaptive recommendation services are designed for learning activity sequence,learning partners and similar resources.The recommendation of learning activity sequence based on learner style characteristics and knowledge level in learner model is proposed.Recommend learning partners based on learning behavior analysis in the learning process;The branch hybrid recommendation strategy based on user collaborative filtering recommendation algorithm is used to recommend similar resources and customize learning resources,so as to realize adaptive recommendation of learning resources.（3）Design and implement the "Zhiyou Recommendation" system for online learning resources.Firstly,analyze the requirements and feasibility of the system according to the principles of software engineering,then design the system architecture,functional modules and database,and finally develop the system to realize the We Chat applet application of "Zhiyou Recommended" on the mobile terminal to assist learning online learning.（4）Analyze the application effect of learning resource recommendation system.This paper analyzes the application effect of online learning resource recommendation system through the experimental research on the application of system assisted teaching and learning.The experiment adopts the methods of comparative analysis of academic performance,online learning behavior analysis,interview and questionnaire survey.Spss software is used for statistical analysis of experimental data.It is found that the use of the system can promote the efficiency of learning resource recommendation,optimize the learning process and improve the online learning effect.The resuts of this study show that the adaptive recommendation system of online learning resources plays a positive role in promoting the adaptive recommendation of learning resources and the improvement of online learning efficiency.In the process of learning,the recommendation system can be close to the needs of learners and push learning resources suitable for learners’ characteristics and learning status,which can alleviate the problem of "learning loss" to a certain extent and improve the efficiency of learning resource recommendation.The system ADAPTS to the arrangement of recommended activities,optimizes the learning process,promotes the improvement of online learning efficiency,and has a positive impact on learners’ sense of learning experience and learning attitude,adding a lot of fun to learning in the learning process.