The Design And Application Of Personalized Learning Strategies In University Computer Foundation

Not only the development of mobile Internet technology and education informatization requires education reform,but also creates conditions for education reform and provides an environment.That learners with personalized learning services use educational data mining technology to has become a popular topic for experts and scholars in the field of education in recent years.In traditional teaching,under limited teaching resources,teachers cannot implement individualized teaching for learners' individual differences.Through the analysis of students' current cognitive level test results,how to deeply integrate data mining technology and education,to provide corresponding learning resources,is a challenge for educational information and education reform to relevant learning resources,implementing individualized teaching in accordance with individual aptitude precising services and promoting the individualized development of student.Thesis is based on the MOOC platform and combines the teaching practice in "University Computer Foundation" to explore the design and application of personalized learning strategies.Thesis has five chapters.The first chapter describes the background,content and significance of the research,and the status of the MOOC platform,the "University Computer Foundation" course and the recommendation of personalized learning resources at China and abroad.The second chapter mainly introduces the related concepts,theoretical basis and techniques.The third chapter introduces the design of personalized learning strategies.It is mainly composed of three parts: Firstly,a knowledge structure diagram is based on the knowledge points of the curriculum and its logical relationship.Secondly,according to the questions-knowledge matrix and the students' answer matrix,the knowledge of students' knowledge is judged,and the topological sorting is used to generate the sequence that the students haven't mastered the knowledge points.Finally,according to the students' knowledge,the collaborative filtering recommendation algorithm is adopted to recommend the corresponding learning resources to students so as to realize personalized teaching.The fourth chapter conducts case studies on the practical research of personalized learning strategies in "University Computer Foundation",and analyzes the practical effects from the four aspects of students' classroom behavior performance,work performance,test scores,and questionnaire survey.The fifth chapter summarizes the research results and deficiencies of thesis,looking forward to the following the research work.The practical research shows that on the one hand,personalized learning strategies can provide feedback information for students' learning situations in time,and can also recommend corresponding learning resources according to their own weak points,then improving students' learning effects.On the other hand,this study provides some theoretical guidance and basis for the development of the "University Computer Foundation" courses and the optimization of teaching.