Research And Construction Of Mobile Learning Invironment Based On Intelligent Recommendationg

With the advancement of educational informationization,the mobile learning concept enables learners to learn at anytime and anywhere with the support of mobile devices and technology.It plays a crucial role in improving the efficiency of mobile learning for learners that construct an efficient mobile learning environment so that it can intelligently recommend learning resources that meet the development level for learners.The combination of reinforcement learning technology with the recommendation system can effectively alleviate such problems while guaranteeing the recommendation effect.However,traditional content-based and collaborative filtering recommendation algorithms often face the problem of sparse data and cold-start,which affects the reliability of the recommendation system.In addition,the current research on development of mobile learning environment is mainly focused on traditional application and web platform,which has a cumbersome installation and registration process,as well as environmental compatibility and other issues.As a new application form,WeChat Mini Programs provide a new possibility for the construction of mobile learning environment because of its download-free and cross-platform characteristics.Through the analysis of mobile learning theory and the development process of WeChat Mini Programs,a mobile learning environment WeChat Mini Program with personalized recommendation function guided by the recent development zone theory is designed and constructed.The main work includes:(1)Design the intelligent recommendation algorithm.In data preprocessing,under the guidance of the theory of ZPD(zone of proximal development),combined with the maximum likelihood estimation method and the characteristics of normal distribution,this paper quantifies the individual development level and exercise difficulty of the learners,respectively,to achieve the model construction.In the aspect of recommendation algorithm,design environment,action,reward function and other important parameters of reinforcement learning,and a personalized learning resource recommendation algorithm based on reinforcement learning is proposed.The experimental results show that the recommendation algorithm can effectively recommend learning resources for learners that meet their development level.(2)Build a mobile learning environment.By analyzing the requirements of mobile learning environment,according to the development principle of WeChat Mini Programs,design and implement the function module,database and user interface of the system.The intelligent recommendation algorithm designed is applied to exercise recommendation module.Finally,a fully functional mobile learning environment WeChat Mini Program is built,and each system has been tested.Result shows that each module of the system functions normally,the cloud server has sufficient capacity to carry,and it can provide a good environment for mobile learners.