Optimization of Classroom Teaching Quality Based on Multimedia Feature Extraction Technology
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| Title: | Optimization of Classroom Teaching Quality Based on Multimedia Feature Extraction Technology |
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| Language: | English |
| Authors: | Lin Zhu, Shujuan Xue |
| Source: | International Journal of Web-Based Learning and Teaching Technologies. 2024 19(1). |
| Availability: | IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/ |
| Peer Reviewed: | Y |
| Page Count: | 11 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Multimedia Instruction, Video Technology, Technology Uses in Education, Information Storage, Information Retrieval, Databases, Accuracy, Interaction, Teacher Effectiveness, Instructional Effectiveness, Metadata |
| DOI: | 10.4018/IJWLTT.336851 |
| ISSN: | 1548-1093 1548-1107 |
| Abstract: | In this article, the research of multimedia teaching video content feature extraction is carried out. According to the file structure, data type, and storage mechanism of the teaching video, a program is developed to automatically extract the structural features of the teaching video content, and a storage and retrieval database is established. The research results show that the accuracy rate of various videos compiled through genie 8.0 for teaching videos exceeds 94%. The recall rate of various videos exceeds 95%. The accuracy and recall of advertisements have reached 100%. Among the elements of teaching video content features, the number of graphs is the highest, followed by film clips, accounting for 14.18. Image, vivid, and interactive multimedia teaching video technology has greatly improved teaching effectiveness, promoting students to better understand and remember knowledge points. The research results provide theoretical data support for multimedia feature extraction to optimize classroom teaching quality. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1428077 |
| Database: | ERIC |
| Abstract: | In this article, the research of multimedia teaching video content feature extraction is carried out. According to the file structure, data type, and storage mechanism of the teaching video, a program is developed to automatically extract the structural features of the teaching video content, and a storage and retrieval database is established. The research results show that the accuracy rate of various videos compiled through genie 8.0 for teaching videos exceeds 94%. The recall rate of various videos exceeds 95%. The accuracy and recall of advertisements have reached 100%. Among the elements of teaching video content features, the number of graphs is the highest, followed by film clips, accounting for 14.18. Image, vivid, and interactive multimedia teaching video technology has greatly improved teaching effectiveness, promoting students to better understand and remember knowledge points. The research results provide theoretical data support for multimedia feature extraction to optimize classroom teaching quality. |
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| ISSN: | 1548-1093 1548-1107 |
| DOI: | 10.4018/IJWLTT.336851 |
