| In recent years,the automobile industry has developed rapidly,and China has become the world’s largest automobile producer and consumer market.As of September 2020,China’s car ownership has reached 281 million.With the increase in car ownership year by year,car maintenance and repairs need more support from practitioners.The establishment of the auto repair major in secondary vocational colleges is precisely through the form of vocational education to provide the society with technical personnel in the field of auto repair.How to help students majoring in automobile maintenance in secondary vocational colleges improve their perception and understanding of what they have learned is a common concern for educators.The application and popularization of Internet technologies such as artificial intelligence and big data have brought a new integrated experience to many industries,and the form of "Internet + education" has also entered secondary vocational colleges,guiding the innovation of secondary vocational teaching models and content.The maturity of knowledge graphs and related technologies of recommendation systems makes it possible for students to learn in a personalized way.This thesis focuses on the complex knowledge points of automobile maintenance in secondary vocational colleges,students have a weak sense of the overall content of what they have learned,and the lack of a system of automobile maintenance cases.The relevant knowledge points and maintenance cases of automobile maintenance in secondary vocational colleges are sorted out,Using computer technology to construct a secondary vocational auto repair knowledge map,and design a secondary vocational auto repair knowledge map recommendation system for teaching.The main research of the thesis includes three parts: the construction of knowledge graph of automobile maintenance professional knowledge,the research of knowledge recommendation strategy and the application of knowledge graph recommendation system in teaching.The full text mainly uses Python as a development tool to integrate various technologies,Neo4 j as a graph database to build a knowledge graph,Gensim library related functions to implement recommendation strategies,and Python GUI to design a human-computer interaction interface.The final design form is to produce a secondary vocational automobile The recommendation system for repairing knowledge graphs can automatically recommend maintenance plans based on knowledge graphs and related auto repair case articles for students according to the questions input by students.There are three main conclusions and results of the thesis:The first is to design and successfully construct a knowledge map of automobile maintenance in secondary vocational colleges,which provides a method for how to construct a knowledge map of automobile maintenance professional knowledge and knowledge maps of other fields,and also provides a basic knowledge base for further recommendation systems.The second is to develop a secondary vocational auto repair knowledge map recommendation system.The system first segmentation of students’ questions and questions,obtains keywords for students’ questions,analyzes the intentions of students’ questions,and finally designs retrieval and recommendation functions.The system can answer the questions asked by students,automatically recommend overhaul plans based on knowledge graphs,and related auto repair case articles for students,so as to solve the difficulties of students’ independent learning and knowledge point learning.Third,this article proposes a secondary vocational auto repair teaching model based on the knowledge map recommendation system,and designs teaching experiments to verify that under this teaching mode,teachers and students can effectively improve student performance through the rational use of secondary vocational auto repair knowledge map recommendation system.It is beneficial to secondary vocational auto repair education. |
PDF Full Text Request