Research And Application Of Teaching Management Platform Based On Knowledge Graph And Gamification

With the advent of the era of Industry 4.0,traditional industrial update rate has accelerated.Huge amount of data instead of the corresponding business that has played a decisive role in all walks of life.The data has become a national basic strategic resource,and big data is increasingly exerting an important influence on the education industry and economic operating mechanism.At present,there are many problems in the development and application of big data,such as imperfect data sharing,questioning about authenticity of data,incomplete data information,etc.Educational data has typical big data features such as large data volume,fast data growth,unstructured,and high value.At the same time,the sources of educational big data are widely dispersed,the correlation between data is high,and the characteristics of high speed changes,which increases the difficulty of integrating,analyzing and predicting educational data.The teaching of human-computer interaction in the classroom has a strong teaching significance for the universities[1].Not only mobilized the enthusiasm of the students in the classroom,but also produced a large amount of teaching interaction data,so that teachers can track student learning status base on student learning data and provide teaching assistance timely.At the same time,gamification classrooms also provide students with a personalized learning model to improve their own learning efficiency.This paper confirms the research methods by investigating the research methods of other universities,and studies how the university analyzes and uses student learning data and interactive data,including student class learning data,study behavior data from MOOC,and school card activity data.These multi-source data in the analysis and processing still did not get the requirements of intelligence.Therefore,this paper uses more human-computer interaction smart devices and gamification mechanisms to acquire the student's learning interaction data in the classroom,then realizing real-time data acquisition and real-time feedback,and subverting the traditional classroom model.In class,using smartphones to send"barrage" and "shake" operations to teachers' PPT,students use their mobile phones to interact of data and behaviors with their teacher,and record students'interaction data and unclear knowledge.After class,they use the laptop to log into the gamification platform which uses the "splitting" and "combining" cards of knowledge points to provide students personalized pre-learning habit review patterns.Students can choose own learning style according to their own circumstances.Through these two interaction methods,a large number of students' process behavior data were obtained,also the questionnaire surveys to meet the requirements of the experiment to investigate student's basic information and related life data.Based on the data,the platform will show the data to the user by means of a dashboard.The student's persona is portrayed through the questionnaire data of the student.The metadata model supporting multi-source heterogeneous data is designed through learning data,and a knowledge graph based on the entity relationship is constructed.The platform also uses big data processing algorithms and multiple analysis models.Using the distance model in knowledge base knowledge base and student knowledge base to structurally represent entities and relationships.There is a clear weight comparison between entities and various attributes.It also facilitates the intelligent recommendation between students and students,students and courses.Through the analysis results of the data,the feedback data and the attribute with the largest weight are brought back to the classroom to improve students' learning methods[2].The main content of this article is divided into six parts.Firstly,we shared the state of smart devices in the classroom and the application of teaching data in China and abroad,and confirmed the importance of teaching data for students' learning.On this basis,we described the human-computer interaction combined with gaming platforms and data processing technologies.After that,this paper introduces the implementation process of smart devices in the classroom and after class,including the requirements,design and development of the platform system.Finally,data processing is performed on student interact data to construct persona and smart recommendation for students.