APPLYING IMAGE AND VIDEO PROCESSING IN ENGLISH EDUCATION: A TECHNOLOGY-ENHANCED LEARNING FRAMEWORK.
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| Title: | APPLYING IMAGE AND VIDEO PROCESSING IN ENGLISH EDUCATION: A TECHNOLOGY-ENHANCED LEARNING FRAMEWORK. |
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| Authors: | LE HAN1 helen_2423@126.com |
| Source: | Scalable Computing: Practice & Experience. Jul2025, Vol. 26 Issue 4, p1740-1753. 14p. |
| Subjects: | Class size, Cognitive styles, Video processing, Learning, Interactive learning |
| Abstract: | Image and video processing in English training is a pioneering technology-enhanced learning strategy which addresses 21st-century student needs. This paradigm’s ability to accommodate today’s multimedia-driven learners’ demands makes it crucial. Such a system requires strong infrastructure, teacher training, scalable computing resources, and adaptive content for diverse learning styles. This research proposes the Smart Multimodal Enhanced Interaction Learning Framework (SMEILF), which takes advantage on multimodal content’s strengths. By making learning more interactive, SMEILF intends to boost students’ engagement, comprehension, and memory. The current research examines SMEILF, a comprehensive system that uses real-time image and video processing for personalised feedback and adaptive learning routes. SMEILF uses interactive language classes, pronunciation training, and contextual video analysis. Simulation analysis demonstrates the framework works and could increase learning, this research contributes to technology-enhanced learning by offering a scalable, adaptive, and student-centered approach to English training. The proposed method increases the learning engagement ratio by 98.5%, pronunciation accuracy ratio by 97.6%, scalability ratio by 99.2%, content accessibility ratio by 92.9%, and teacher and student satisfaction ratio by 95.8% compared to other existing methods. The proposed method increases the learning engagement ratio by 98.5%, pronunciation accuracy ratio by 97.6%, scalability ratio by 99.2%, content accessibility ratio by 92.9%, and teacher and student satisfaction ratio by 95.8% compared to other existing methods. [ABSTRACT FROM AUTHOR] |
| Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience 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.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 185633752 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: APPLYING IMAGE AND VIDEO PROCESSING IN ENGLISH EDUCATION: A TECHNOLOGY-ENHANCED LEARNING FRAMEWORK. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22LE+HAN%22">LE HAN</searchLink><relatesTo>1</relatesTo><i> helen_2423@126.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Scalable+Computing%3A+Practice+%26+Experience%22">Scalable Computing: Practice & Experience</searchLink>. Jul2025, Vol. 26 Issue 4, p1740-1753. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Class+size%22">Class size</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+styles%22">Cognitive styles</searchLink><br /><searchLink fieldCode="DE" term="%22Video+processing%22">Video processing</searchLink><br /><searchLink fieldCode="DE" term="%22Learning%22">Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Interactive+learning%22">Interactive learning</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Image and video processing in English training is a pioneering technology-enhanced learning strategy which addresses 21st-century student needs. This paradigm’s ability to accommodate today’s multimedia-driven learners’ demands makes it crucial. Such a system requires strong infrastructure, teacher training, scalable computing resources, and adaptive content for diverse learning styles. This research proposes the Smart Multimodal Enhanced Interaction Learning Framework (SMEILF), which takes advantage on multimodal content’s strengths. By making learning more interactive, SMEILF intends to boost students’ engagement, comprehension, and memory. The current research examines SMEILF, a comprehensive system that uses real-time image and video processing for personalised feedback and adaptive learning routes. SMEILF uses interactive language classes, pronunciation training, and contextual video analysis. Simulation analysis demonstrates the framework works and could increase learning, this research contributes to technology-enhanced learning by offering a scalable, adaptive, and student-centered approach to English training. The proposed method increases the learning engagement ratio by 98.5%, pronunciation accuracy ratio by 97.6%, scalability ratio by 99.2%, content accessibility ratio by 92.9%, and teacher and student satisfaction ratio by 95.8% compared to other existing methods. The proposed method increases the learning engagement ratio by 98.5%, pronunciation accuracy ratio by 97.6%, scalability ratio by 99.2%, content accessibility ratio by 92.9%, and teacher and student satisfaction ratio by 95.8% compared to other existing methods. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience 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: 10.12694/scpe.v26i4.4693 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1740 Subjects: – SubjectFull: Class size Type: general – SubjectFull: Cognitive styles Type: general – SubjectFull: Video processing Type: general – SubjectFull: Learning Type: general – SubjectFull: Interactive learning Type: general Titles: – TitleFull: APPLYING IMAGE AND VIDEO PROCESSING IN ENGLISH EDUCATION: A TECHNOLOGY-ENHANCED LEARNING FRAMEWORK. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: LE HAN IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 18951767 Numbering: – Type: volume Value: 26 – Type: issue Value: 4 Titles: – TitleFull: Scalable Computing: Practice & Experience Type: main |
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