Design And Implementation Of A Personalized Education System

With the prevalence and development of mobile Internet,as a new mode of education which uses Internet and information technology,online education is rising gradually.Existing online education system such as MOOC,the fineness of its control on knowledge is still coarser,besides the function of personalized teaching is hardly available,so the weakness is leading to low course completion and poor learning experience.Personalized education system can provide personalized content based on learner's individual properties,so that students can improve their thinking,innovation as well as autonomous learning abilities,then improve the experience of online learning.This thesis studies and brings about a personalized education system based on B/S architecture.Firstly,this thesis introduces the research status of individualized education at home and abroad,and analyzes the problems which could be further explored on the basis of previous studies,then describes the key theories and technologies which are needed to develop the system,meanwhile concepts,theories,advantages and disadvantages of these technologies are analyzed.Next,this thesis carries on the system requirements analysis and overall system design,the feasibility of the system are discussed on the development,Outlines the overall architecture of the system and introduces the mode of online education resources management and divides the system function into several modules,then on the detailed system design stage,the thesis integrates the requirements of every function module and describes the ways of design and implementation of the key function modules of this system.Finally about each function module,a series of tests and analyzes are carried out.The main points of this work includes:(1)Use web crawler to collect knowledge contents about different subjects from the web knowledge base,and analyzes the topic of the contents.Then,on this basis,put forward a method of konwlege point clustering based on the analysis of word frequency.Use this method for the clustering of topics and their related contents,and then construts the hierarchical konwlege graph of its subject.At the same time,build the base of questions for online tests in a similar way.(2)On the basis of the completion of the integration of konwlege points as well as the referred questions.Provide the users of the service of recommendation about subjects and study paths by the analysis of users' learning behaviors.The detailed data about the behaviors of users' learning behaviors include: initial learning data,records of users' tests and history data of browsing,etc.Meanwhile use different recommendation algorithms in different situations according to the requirements of the system,the advantages and disadvantages of different recommendation algorithms.Massive tests show that the system can basically meet with the requirements of users' personalized needs on learning contents,solve the key problems of the online evaluation of study effect and the recommendation of learning paths.So the system can support users to study at any time and place,improve the study effect and learning experiences effectively.