Research On The Extraction And Organization Of Course Knowledge Points In Big Data Environment

With the coming of the age of big data in Education,the accumulation of curriculum materials resources,and the rapid increase in the variety of courses,and curriculum knowledge constantly updated and changed,making it more difficult to analyze the knowledge points and the efficient selection of knowledge points in a large number of curriculum materials resources,the various forms of curriculum teaching materials,resulting in differences in the knowledge structure of curriculum materials,it makes it more difficult to screen a large number of course materials and organize the teaching materials effectively.Therefore,with the help of data analysis and technical support provided by big data,this thesis puts forward a method of automatic extraction and effective organization of curriculum knowledge points in Big Data environment after studying the relevant viewpoints and methods of curriculum knowledge points and curriculum knowledge organization at home and abroad.This method draws on the successful experience of data mining,text mining and so on in educational data mining,and the main contributions of this dissertation could be described as following:Firstly,this paper analyzes the present situation of knowledge points and the status quo of relationship organization between knowledge points,draws lessons from the application of big data in education,clarifies the existing problems and specific research contents,combined with big data analysis methods and techniques,and proposed a set of system construction framework about the extraction and organization of curriculum knowledge point under the big Data environment,and secondly,this paper deeply studies the guidance of Elaboration theory and knowledge organization theory on the content analysis of teaching materials,analyzes the characteristics and problems of knowledge structure of curriculum materials,and established the model of curriculum knowledge Organization,and finally,adopts the method of course knowledge point extraction based on mixed strategy,combining rule matching,unsupervised clustering,keyword extraction and other methods to extract course knowledge points.This paper uses the method of big data fusion to extract the knowledge points,through calculating the similarity degree between the text content of knowledge points by layer,and according to the similarity of the text content,carries on the statistical analysis to the fusion result to discover laws,organizes the course textbook knowledge structure.Combining with the research content of Elaboration theory,this paper analyzes the knowledge structure of curriculum teaching materials,finds out the characteristics and existing problems of the knowledge structure of curriculum materials,puts forward the method of course knowledge point extraction and organization under the big Data environment,solves the difficult problems of the extraction and organization of curriculum knowledge points under the knowledge structure of different course materials,and The course teaching material of educational psychology is an example to carry on the method experiment,analyzes the result of the experiment process,and verifies the validity and feasibility of each part of the research content.It's aim to further help resource choreography of teaching and the developers of the teaching resource,teachers and other analysis,screening,evaluation of curriculum materials.