Periodical
A Study on Decision Tree Analysis Method of Teaching Quality Improvement for Teachers of Marketing in Higher Education Institutions.
| Τίτλος: | A Study on Decision Tree Analysis Method of Teaching Quality Improvement for Teachers of Marketing in Higher Education Institutions. |
|---|---|
| Συγγραφείς: | Yu, Huaying |
| Πηγή: | Journal of Combinatorial Mathematics & Combinatorial Computing; Dec2025, Vol. 127b, p3847-3865, 19p |
| Θεματικοί όροι: | Marketing education, Data mining, Universities & colleges, Assessment for learning (Teaching model), Effective teaching, Decision trees |
| Περίληψη: | In order to explore the deficiencies in the teaching process of marketing majors in higher vocational colleges and further improve the teaching quality of marketing majors in higher vocational colleges. This paper utilizes the improved ID3 algorithm to construct the SLIQ data mining algorithm to improve the teaching quality of teachers of marketing majors in higher vocational colleges and universities. Using ID3 algorithm to build a decision tree to get the portraits of teachers and students, at the same time, in order to reduce the computational complexity of ID3 algorithm and the problem of multi-value bias, the concept of sample structure vector similarity is introduced, and the degree of information gain is optimized to get a more reasonable decision tree. On this basis, based on the improved ID3 data mining algorithm, a teaching quality assessment system for senior marketing majors based on SLIQ algorithm is designed, which identifies important factors affecting teachers' teaching quality by mining a large amount of data in the teaching process. The AUC value of the SLIQ data mining algorithm is 0.98, which can effectively improve the algorithm's generalization ability, and it has an excellent performance in the teaching quality assessment task. The performance is excellent. In this paper, we systematically identify “the principles of marketing” and “the degree of seriousness of teachers' homework correction” as the key factors to improve the teaching quality of marketing teachers. It provides a scientific basis for improving the quality of teachers' teaching. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Combinatorial Mathematics & Combinatorial Computing is the property of Combinatorial Press 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 | Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Study on Decision Tree Analysis Method of Teaching Quality Improvement for Teachers of Marketing in Higher Education Institutions. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yu%2C+Huaying%22">Yu, Huaying</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Combinatorial Mathematics & Combinatorial Computing; Dec2025, Vol. 127b, p3847-3865, 19p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Marketing+education%22">Marketing education</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Universities+%26+colleges%22">Universities & colleges</searchLink><br /><searchLink fieldCode="DE" term="%22Assessment+for+learning+%28Teaching+model%29%22">Assessment for learning (Teaching model)</searchLink><br /><searchLink fieldCode="DE" term="%22Effective+teaching%22">Effective teaching</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+trees%22">Decision trees</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In order to explore the deficiencies in the teaching process of marketing majors in higher vocational colleges and further improve the teaching quality of marketing majors in higher vocational colleges. This paper utilizes the improved ID3 algorithm to construct the SLIQ data mining algorithm to improve the teaching quality of teachers of marketing majors in higher vocational colleges and universities. Using ID3 algorithm to build a decision tree to get the portraits of teachers and students, at the same time, in order to reduce the computational complexity of ID3 algorithm and the problem of multi-value bias, the concept of sample structure vector similarity is introduced, and the degree of information gain is optimized to get a more reasonable decision tree. On this basis, based on the improved ID3 data mining algorithm, a teaching quality assessment system for senior marketing majors based on SLIQ algorithm is designed, which identifies important factors affecting teachers' teaching quality by mining a large amount of data in the teaching process. The AUC value of the SLIQ data mining algorithm is 0.98, which can effectively improve the algorithm's generalization ability, and it has an excellent performance in the teaching quality assessment task. The performance is excellent. In this paper, we systematically identify “the principles of marketing” and “the degree of seriousness of teachers' homework correction” as the key factors to improve the teaching quality of marketing teachers. It provides a scientific basis for improving the quality of teachers' teaching. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of Combinatorial Mathematics & Combinatorial Computing is the property of Combinatorial Press 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: 10.61091/jcmcc127b-214 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 3847 Subjects: – SubjectFull: Marketing education Type: general – SubjectFull: Data mining Type: general – SubjectFull: Universities & colleges Type: general – SubjectFull: Assessment for learning (Teaching model) Type: general – SubjectFull: Effective teaching Type: general – SubjectFull: Decision trees Type: general Titles: – TitleFull: A Study on Decision Tree Analysis Method of Teaching Quality Improvement for Teachers of Marketing in Higher Education Institutions. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yu, Huaying IsPartOfRelationships: – BibEntity: Dates: – D: 10 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 08353026 Numbering: – Type: volume Value: 127b Titles: – TitleFull: Journal of Combinatorial Mathematics & Combinatorial Computing Type: main |
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