Academic Journal
Design of Teaching Quality Analysis and Management System for PE Courses Based on Data-Mining Algorithm.
| Τίτλος: | Design of Teaching Quality Analysis and Management System for PE Courses Based on Data-Mining Algorithm. |
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| Συγγραφείς: | Li, Sen, Yanrui Luo |
| Πηγή: | Computational Intelligence & Neuroscience; 5/31/2022, p1-9, 9p |
| Θεματικοί όροι: | Courseware, Management information systems, Effective teaching, Information resources management, Total quality management, Distributed algorithms |
| Περίληψη: | Advances in network technology have led to extensive information technology construction work in all walks of life; universities, as a key component of national development, cannot be overlooked in this regard. In today's universities, the Web-based integrated academic management information system is widely used, promoting higher education management system innovation and improving the management level of education departments and teaching management. The traditional management mode is incapable of locating "knowledge" in the mountains of student transcripts, and the original management mode must be improved. In business, finance, insurance, marketing, and other fields, digital exploration technology is widely used. This article describes the design approach for a data mining-based analysis and management system for PE course teaching quality, as well as the application of information technology and data mining technology in PE by combining actual PE teaching in schools, with the goal of realizing a data mining-based PE performance management system to serve PE teaching in schools and improve PE teaching quality. The results show that the time required to find frequent itemsets using a traditional algorithm running on a single machine, as well as the time required to scan the database several times for frequent itemset search in a distributed cluster of 20 computing nodes, is significantly longer than that required by the data mining algorithm. As a result, the proposed sports performance management system is functional, simple, and scalable, with each functional module operating independently and cooperatively, reflecting the concept of "high cohesion and low coupling." [ABSTRACT FROM AUTHOR] |
| Copyright of Computational Intelligence & Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 157189968 RelevancyScore: 916 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 915.923400878906 |
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| Items | – Name: Title Label: Title Group: Ti Data: Design of Teaching Quality Analysis and Management System for PE Courses Based on Data-Mining Algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Sen%22">Li, Sen</searchLink><br /><searchLink fieldCode="AR" term="%22Yanrui+Luo%22">Yanrui Luo</searchLink> – Name: TitleSource Label: Source Group: Src Data: Computational Intelligence & Neuroscience; 5/31/2022, p1-9, 9p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Courseware%22">Courseware</searchLink><br /><searchLink fieldCode="DE" term="%22Management+information+systems%22">Management information systems</searchLink><br /><searchLink fieldCode="DE" term="%22Effective+teaching%22">Effective teaching</searchLink><br /><searchLink fieldCode="DE" term="%22Information+resources+management%22">Information resources management</searchLink><br /><searchLink fieldCode="DE" term="%22Total+quality+management%22">Total quality management</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+algorithms%22">Distributed algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Advances in network technology have led to extensive information technology construction work in all walks of life; universities, as a key component of national development, cannot be overlooked in this regard. In today's universities, the Web-based integrated academic management information system is widely used, promoting higher education management system innovation and improving the management level of education departments and teaching management. The traditional management mode is incapable of locating "knowledge" in the mountains of student transcripts, and the original management mode must be improved. In business, finance, insurance, marketing, and other fields, digital exploration technology is widely used. This article describes the design approach for a data mining-based analysis and management system for PE course teaching quality, as well as the application of information technology and data mining technology in PE by combining actual PE teaching in schools, with the goal of realizing a data mining-based PE performance management system to serve PE teaching in schools and improve PE teaching quality. The results show that the time required to find frequent itemsets using a traditional algorithm running on a single machine, as well as the time required to scan the database several times for frequent itemset search in a distributed cluster of 20 computing nodes, is significantly longer than that required by the data mining algorithm. As a result, the proposed sports performance management system is functional, simple, and scalable, with each functional module operating independently and cooperatively, reflecting the concept of "high cohesion and low coupling." [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Computational Intelligence & Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/2022/6830375 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 1 Subjects: – SubjectFull: Courseware Type: general – SubjectFull: Management information systems Type: general – SubjectFull: Effective teaching Type: general – SubjectFull: Information resources management Type: general – SubjectFull: Total quality management Type: general – SubjectFull: Distributed algorithms Type: general Titles: – TitleFull: Design of Teaching Quality Analysis and Management System for PE Courses Based on Data-Mining Algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Sen – PersonEntity: Name: NameFull: Yanrui Luo IsPartOfRelationships: – BibEntity: Dates: – D: 31 M: 05 Text: 5/31/2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 16875265 Titles: – TitleFull: Computational Intelligence & Neuroscience Type: main |
| ResultId | 1 |