Construction And Application Of Curriculum Knowledge Graph For Intelligent Education

The promulgation of the "Education Informatization 2.0 Action Plan" in2018 has provided theoretical support for the development of emerging technologies such as artificial intelligence,big data,and the Internet of Things in the field of education,promoting innovative exploration of smart education,and guiding a new development direction of education informatization.As one of the artificial intelligence technologies that promote the effective development of intelligent education,knowledge graph plays an important role in displaying knowledge points,establishing learner models,intelligent question answering,and personalized services.Currently,the existing knowledge graph is rarely applied in intelligent education environments,and most of them have problems such as incomplete ontology design,single relationship between knowledge points,poor integration with the classroom,and neglect of updating and maintaining the graph.How to design a comprehensive and complete curriculum ontology and extract curriculum knowledge and relationships using natural language processing technology is one of the difficulties in intelligent education research.Taking the hardware core course "Principles of Computer Composition" in the computer major as an example,the knowledge of this course is abstract and complex,making it difficult to master the overall structure and working principles of computer hardware systems based on the overall situation of the teaching materials.Students’ enthusiasm for learning is generally not high,and the course knowledge graph can effectively organize the course content and help learners form logical associations in their minds.Based on this,this study focuses on the shortcomings of the existing curriculum knowledge graph,building a curriculum knowledge graph,developing a visual query system,and designing teaching models based on the curriculum characteristics and learning needs.The study was conducted from four aspects:First,clarify the current development situation and analyze educational theory.This study sets out from the current development situation of the knowledge graph in the intelligent education environment,and develops research methods and content.Combining theories such as constructivism,relevancy,and the basic structure of disciplines,this paper analyzes the internal relationships between intelligent education and knowledge graph,and lays the technical foundation for knowledge graph and visualization systems by introducing ontology construction,knowledge graph,web crawlers,Neo4 j graph data,and D3 tools.Second,construct a curriculum ontology based on the characteristics of the curriculum.Taking the educational knowledge graph as a prototype,this paper expounds the principle and process of constructing the curriculum knowledge graph.According to the knowledge characteristics and teaching difficulties of the course "Principles of Computer Composition",the method of constructing the course ontology is analyzed and the model is designed.On this basis,the Protégé tool and the "seven step method" are used to construct the curriculum goal ontology,curriculum knowledge point ontology,and curriculum resource ontology of "Principles of Computer Composition".Third,select the course content and construct a knowledge graph.Taking the course ontology as the underlying architecture,using a semi-automatic construction method,and using network resources and teaching materials as data sources,a comparative experiment was conducted to set up three models:CRF,Bi LSTM,and Bi LSTM-CRF.The results showed that the Bi LSTM-CRF model had the best effect,with an F1 value of 87.32%.Therefore,a combination of Bi LSTM-CRF model and artificial rules is used to extract curriculum knowledge points,and dependency syntax analysis,artificial participation,and other methods are used to extract the relationship between knowledge points.The extracted results are fused and stored in the Neo4 j graph database,initially forming a curriculum knowledge graph.Due to the fact that the quality of the knowledge graph cannot be guaranteed,the knowledge graph was processed from both quality assessment and update maintenance,resulting in 724 knowledge points and 1985 sets of relationships.Fourth,build a query system and design a teaching plan.According to the actual teaching requirements and students’ cognitive characteristics,a visual query system is developed based on the Knowledge graph of the course,and the map display,relationship display,search and query functions are realized by using D3 tools,Neo4 j Graph database,etc.By applying the Knowledge graph of the curriculum to the intelligent education environment,the design of the teaching scheme helps to build the learner’s knowledge system.At the same time,the visual query system is used in a small scale.The questionnaire is distributed to investigate the learners’ satisfaction with the use experience,effectiveness,learning motivation,learning effect and resources of the system,and the teachers’ satisfaction and suggestions with the system are investigated through interviews.The experimental results show that the system can effectively help learners improve their learning confidence,interest,and initiative,enhance learning effectiveness,improve learning efficiency,and provide them with high-quality learning resources,with good application value.