A Brief Analysis of the Key Technologies and Applications of Educational Data Mining on Online Learning Platform
With the rapid development of the Internet and communication technology, online education has drawn more and more attention, online learning platforms, on the other hand, store massive learner behavioral data and educational data. How to effectively analyze and utilize the data to improve the quality of online education has become a key issue urgently needed to be solved in the field of big data in education(BDE), educational data mining(EDM) is exactly an effective and practical method and means of applying BDE. Therefore, EDM is an important academic research hotspot in the field of EDM. Firstly, the paper introduces the basic concepts of BDE, EDM and online learning platform, and then elaborates on the process of how educational data mining transforms raw data into knowledge. Finally, the key technologies of data mining are classified according to their uses, and gives its application in online education scene. The paper can provide some guidance for the research and application of educational data mining based on online education.
Big data on education (BDE) is a subset of big data, which refers to data in education. In fact, big data is a nebulous concept that has not yet formed an accepted definition. Even so, there is a difference between big data and past data, and its basic connotation can be summed up in 4V(Volume, Variety, Value and Velocity)of which specific meanings. In recent years, with the popularization of educational informationization and the rise of new online education model represented by MOOC, more and more researchers are concerned about the EDM. Educational data mining EDM is actually the application of data mining technology in education and the object of analysis and processing is to BDE, its purpose is to find out and solve the problems in education by using the key technologies of data mining to mine big data in the online learning platform, to obtain the important and valuable information in the teaching process and to improve the quality of teaching and learning.
This paper mainly includes two aspects: educational data mining process and key mining technology classification: the educational data mining process mainly explains how to extract raw data from the database to provide value for education decision-makers and learnerskey mining technology classification is to analyze the technologies used in educational data mining process, the paper not only categorizes these technologies but also attempts to explain the differences and connections between them, namely, when different technologies should be applied to a scenario. Finally, we put forward some prospects of EDM in online education.
Big data is of revolutionary significance to online education. With such huge and complicated data on the online learning platforms, it is particularly important to study and apply these BDE. From the perspective of academic research and technology application, the paper elaborates the basic concepts of BDE, EDM and online education, the detailed process of educational data mining, the classification of educational data mining technologies, and the need to pay attention in the process of mining. For example, different algorithms are selected according to different application scenarios, and examples of specific scenarios used by some key technologies are given. The purpose of this paper is to enable other researchers or educators to gain a better understanding of the ways in which educational data mining is used in the education of big data and better utilize educational data mining techniques to improve the quality of online education. The development of big data has brought many opportunities for online education, the emergence of new mining technologies will certainly provide better methods and means for the application of EDM in the field of online education. Using these new technologies will also lead to more scientific analysis and higher-value knowledge, and better service for online education. However, care must be taken to address the managerial, ethical and technical challenges and limitations of educational data mining, all of which need to further strengthen the research on the educational data mining of online education.
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