A Framework for the Integration of Mobile Technology and Artificial Intelligence with the Aim of Evaluating the Quality of Teaching in Higher Vocational Education.
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| Title: | A Framework for the Integration of Mobile Technology and Artificial Intelligence with the Aim of Evaluating the Quality of Teaching in Higher Vocational Education. |
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| Authors: | Wang, Junxiang1 2006110054@sjzpt.edu.cn |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 3, p4-17. 14p. |
| Subjects: | Artificial intelligence, Mobile computing, Acquisition of data, Outcome-based education, Machine learning, Effective teaching, Vocational education |
| Abstract: | Against the backdrop of global digital transformation in vocational education, the practice-oriented and skill-centered nature of higher vocational education poses challenges for teaching quality evaluation, including fragmented data collection across diverse instructional settings such as theoretical courses, practical training, and internship placements and the lack of effective methods for capturing unstructured operational data. Skill assessments also remain dependent on subjective human judgment, limiting objectivity and quantifiability of performance indicators such as the compliance of electrical wiring tasks. Although mobile technology and artificial intelligence (AI) offer potential solutions, existing approaches lack a systematic evaluation paradigm aligned with vocational education needs. Current research remains limited by insufficient scenario adaptability and misalignment between technological functions and pedagogical requirements. To develop a teaching quality evaluation system for vocational education that integrates mobile technology and AI, the core research questions include the construction of a system framework adaptable to diverse instructional scenarios, the implementation pathways of key technical modules, and the verification of the system's effectiveness. A four-dimensional framework--data acquisition, intelligent analysis, feedback optimization, and management coordination--was established, and a prototype system featuring full-scenario mobile data capture and AI-based skill quantification was implemented. Quasi-experimental studies in three vocational institutions of varying types demonstrate the system's ability to address contextual and technical bottlenecks. The proposed scenario--technology--education alignment paradigm provides a reusable technical solution and empirical basis for quality assurance in vocational education. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies 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: 191627699 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Framework for the Integration of Mobile Technology and Artificial Intelligence with the Aim of Evaluating the Quality of Teaching in Higher Vocational Education. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Junxiang%22">Wang, Junxiang</searchLink><relatesTo>1</relatesTo><i> 2006110054@sjzpt.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Interactive+Mobile+Technologies%22">International Journal of Interactive Mobile Technologies</searchLink>. 2026, Vol. 20 Issue 3, p4-17. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+computing%22">Mobile computing</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br /><searchLink fieldCode="DE" term="%22Outcome-based+education%22">Outcome-based education</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Effective+teaching%22">Effective teaching</searchLink><br /><searchLink fieldCode="DE" term="%22Vocational+education%22">Vocational education</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Against the backdrop of global digital transformation in vocational education, the practice-oriented and skill-centered nature of higher vocational education poses challenges for teaching quality evaluation, including fragmented data collection across diverse instructional settings such as theoretical courses, practical training, and internship placements and the lack of effective methods for capturing unstructured operational data. Skill assessments also remain dependent on subjective human judgment, limiting objectivity and quantifiability of performance indicators such as the compliance of electrical wiring tasks. Although mobile technology and artificial intelligence (AI) offer potential solutions, existing approaches lack a systematic evaluation paradigm aligned with vocational education needs. Current research remains limited by insufficient scenario adaptability and misalignment between technological functions and pedagogical requirements. To develop a teaching quality evaluation system for vocational education that integrates mobile technology and AI, the core research questions include the construction of a system framework adaptable to diverse instructional scenarios, the implementation pathways of key technical modules, and the verification of the system's effectiveness. A four-dimensional framework--data acquisition, intelligent analysis, feedback optimization, and management coordination--was established, and a prototype system featuring full-scenario mobile data capture and AI-based skill quantification was implemented. Quasi-experimental studies in three vocational institutions of varying types demonstrate the system's ability to address contextual and technical bottlenecks. The proposed scenario--technology--education alignment paradigm provides a reusable technical solution and empirical basis for quality assurance in vocational education. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies 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: 10.3991/ijim.v20i03.60251 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 4 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Mobile computing Type: general – SubjectFull: Acquisition of data Type: general – SubjectFull: Outcome-based education Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Effective teaching Type: general – SubjectFull: Vocational education Type: general Titles: – TitleFull: A Framework for the Integration of Mobile Technology and Artificial Intelligence with the Aim of Evaluating the Quality of Teaching in Higher Vocational Education. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Junxiang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 18657923 Numbering: – Type: volume Value: 20 – Type: issue Value: 3 Titles: – TitleFull: International Journal of Interactive Mobile Technologies Type: main |
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