Research on Mining of Applied Mathematics Educational Resources Based on Edge Computing and Data Stream Classification

Lu, Liping; Zhou, Jing

doi:10.1155/2021/5542718

Cited by 32 publications

(12 citation statements)

References 39 publications

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“…e cognitive diagnostic model uses these scores, along with other teaching information, to make inferences about students' abilities and generate cognitive reports that are returned to students. Students can carry out the targeted training based on cognitive reports to check and fill gaps [14].…”

Section: Methodsmentioning

confidence: 99%

On the Intelligent Computing Model of Diagnosis Teaching in Preschool Education in Colleges and Universities under the Background of Big Data

Ding¹

2022

Computational Intelligence and Neuroscience

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In order to infer the cognitive state of students and provide teachers with the potential learning state of students, a diagnostic teaching model for preschool education in colleges and universities under the background of big data is proposed. By increasing students’ programming ability and modeling students’ theoretical and practical abilities at the same time, the cognitive diagnosis is introduced into the field of computer teaching, so as to make it applicable to computer classrooms and provide students’ cognitive information needed for teaching. The experimental results show that the advantages of the CDF-CSE approach gradually emerge as the training data become sparse (the proportion of training data decreases from 80% to 20%). In the combined questions of the three datasets, when the training set is 20% and MAE is used as the criterion, the CDF-CSE model improves by 47.8%, 65.8%, and 49.8%, respectively, compared with the other methods that perform best on the training set. When the number of questions is small, the CDF-CSE model improves by 37.8%, 42.5%, and 27.7% on RMSE on three datasets, respectively, compared with the best-performing other methods. When there are more questions, it has 32.3%, 36.5%, and 45.6% improvement, respectively. It is concluded that this model can accurately predict students’ performance in computer courses and provide detailed and rich cognitive reports.

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Section: Methodsmentioning

confidence: 99%

On the Intelligent Computing Model of Diagnosis Teaching in Preschool Education in Colleges and Universities under the Background of Big Data

Ding¹

2022

Computational Intelligence and Neuroscience

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“…e upper layer is business layer, which is composed of virtual machine cluster. Connecting with the external network and completing various tasks are all completed by the business layer, and the support layer is only used to carry the business layer, logically isolated from the external network [13]. e overall architecture of the education information platform includes hardware and software, and a virtual machine is also used for control analysis to achieve the effect of platform application.…”

Section: E Overall Architecture Of the Education Informationmentioning

confidence: 99%

Research on Educational Information Platform Based on Cloud Computing

Xia

Huang

et al. 2021

Security and Communication Networks

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The traditional method only pays attention to hardware construction and ignores the data processing steps, which leads to high redundant resource occupancy rate, untimely resource sharing, and low platform data safety factor. In order to solve this problem, this paper establishes an educational information platform based on cloud computing. The platform gives the overall structure of the education information platform, including the business layer and the support layer. Then the external interface is designed. Based on the MySQL database interface, users are allowed to use custom data formats and storage management modes to ensure flexibility in using data resources and improve the compatibility between smart terminals and virtual machines through the remote desktop terminal architecture. Through the educational data compression and educational resource sharing model, the generation of redundant messages is reduced, thereby realizing the design of the educational information platform. Experimental results show that this method can effectively reduce the occupancy rate of redundant resources, save network bandwidth, and improve the data safety factor of the platform. The resource sharing time is always less than 2.0 s, which verifies the effectiveness of the method

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“…Lu and Zhou wrote this article to focus on the development of applied technology for the extraction of mathematical education. Second, use algorithms to extract information and classify and integrate a large number of trained professionals [8]. Although the analysis is very accurate, there are some shortcomings in the analysis of physical education.…”

Section: Related Workmentioning

confidence: 99%

Application of Data Mining Technology in Public Welfare Sports Education in the Era of Artificial Intelligence

Dong

Huang

Lin³

2021

Mobile Information Systems

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Data mining refers to extracting the implicit prediction information from a massive dataset. It has very application prospects. Some data mining tools can develop things. The purpose of this article mainly discusses the public welfare sports education in the artificial intelligence era. The article discusses the research background and significance, development of education data mining, and decision tree technology and enumerates the application of education data mining in real life. The concept of educational data mining is given, and several common typical decision tree algorithms and their connections and differences are described; then, the concepts of multivalue decision tables and decision trees are discussed in detail. This article aims to build a nonprofit physical education system to manage and analyze the attendance data of students’ physical health assessment, so as to improve the enthusiasm of students to exercise, such as BP neural network, decision tree classification algorithm, and cluster analysis, discusses the calculation and analysis process of the relevant body side data of the sports teaching platform, and emphatically discusses and analyzes the application effect of data mining technology in public welfare sports teaching. In addition, this article has built a public welfare physical education system, allowing us to clearly understand various factors that affect students’ exercise and the relationship between various project indicators. Based on these data, educators can adjust technical means. Experimental results can efficiently and conveniently understand the pass rate of students in various sports. The pass rates of students in the six tests, grip strength, and sitting forward bending were 58%, 65%, 78%, 78%, 85%, and 65%, respectively. Using mathematical methods and computer technology, we can dig out valuable education management information from massive education data, so as to provide a reference for improving school enrollment.

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Research on Mining of Applied Mathematics Educational Resources Based on Edge Computing and Data Stream Classification

Cited by 32 publications

References 39 publications

On the Intelligent Computing Model of Diagnosis Teaching in Preschool Education in Colleges and Universities under the Background of Big Data

On the Intelligent Computing Model of Diagnosis Teaching in Preschool Education in Colleges and Universities under the Background of Big Data

Research on Educational Information Platform Based on Cloud Computing

Application of Data Mining Technology in Public Welfare Sports Education in the Era of Artificial Intelligence

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