Teaching Mode Based on Educational Big Data Mining and Digital Twins

Abstract

Data mining technology has gradually become an important data analysis and knowledge discovery technology widely used in many modern industries. Data mining is a technique to find its regularity from a large amount of data by analyzing each data. It mainly includes three steps: data preparation, regularity search, and regularity representation. Data preparation is to select the required data from relevant data sources and integrate them into a data set for data mining; regular search is to find out the regularity contained in the data set by a certain method; regular expression is to be as user-readable as possible. The way of understanding (such as visualization) will represent the found patterns. This research mainly discusses the improvement of teaching mode based on digital twin-based education big data mining. Through the research on the basic principles of data mining and digital twin technology, the student evaluation tool module based on digital twin and the relevant data analysis tool module of students based on digital twin education big data mining are developed. Data mining is carried out from the data of student performance, personal basic information, and evaluation information to find the correlation between various factors, find the hidden laws, and provide support for teaching decision-making. This paper also solves the problem of frequent communication with remote databases according to the characteristics of the database data required by students and improves the efficiency and scalability of education big data mining technology based on digital twins. The goal of the virtual interactive system of the digital twin-based CNC platform is to have both three-dimensional real-time monitoring and remote control functions based on a three-dimensional virtual CNC panel. This research integrates the three-dimensional real-time monitoring and remote control of the virtual interactive system, analyzes the system operation process, develops the system interface, and improves the system sub-functions; it builds an experimental environment, conducts example tests on various functions of the digital twin platform virtual interactive system, and performs virtual interactions system performance indicators are analyzed. 60% of students believe that their innovation ability has been improved after the implementation of the digital twin teaching model; 50% of students believe that their self-evaluation ability has been improved. Applying digital twin’s educational big data mining to student information management, university teaching evaluation, student performance analysis, and examination system, it has played a very good guiding role in improving the level of school teaching management.