Analysis and research on the integration of education, technology and industry in smart education

Under the wave of digitalization and intelligence, smart education is becoming an important force to promote educational modernization, promote educational equity and improve educational quality. This manuscript elucidates the principle, features, and current progress of intelligent learning, with a...

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Main Authors: Shao Haiyan, Lv Jie, Sun Xuan, Wang Na, Wang Peng, Zhu Dongqing, Xue Hao, Chen Bin, Ma Yuzhen
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
Series:ITM Web of Conferences
Subjects:
Online Access:https://www.itm-conferences.org/articles/itmconf/pdf/2025/08/itmconf_emit2025_01027.pdf
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author Shao Haiyan
Lv Jie
Sun Xuan
Wang Na
Wang Peng
Zhu Dongqing
Xue Hao
Chen Bin
Ma Yuzhen
author_facet Shao Haiyan
Lv Jie
Sun Xuan
Wang Na
Wang Peng
Zhu Dongqing
Xue Hao
Chen Bin
Ma Yuzhen
author_sort Shao Haiyan
collection DOAJ
description Under the wave of digitalization and intelligence, smart education is becoming an important force to promote educational modernization, promote educational equity and improve educational quality. This manuscript elucidates the principle, features, and current progress of intelligent learning, with a particular emphasis on the examination of digital education strategies from different nations. From multiple dimensions, the differences between traditional education and smart education are compared and analyzed. The analysis examines the specific progression of intelligent education across different nations, emphasizing the fusion of educational and technological fields, the convergence between education and the industrial sector, and the tripartite integration of industry, academia, and research, along with the challenges. The focus of this manuscript is on pioneering integration strategies through case-based teaching, the joint educational framework of industry-academic convergence, the development of a multifaceted assessment approach, and the new ‘teacher-machine-student’ teaching model. The manuscript also discusses the future development trend of smart education. Research shows that the deep integration of smart education requires multi-party collaboration, continuous innovation of teaching models, further improvement of the evaluation system, and the fostering of creative individuals equipped for the demands of forthcoming societal challenges.
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spelling doaj-art-41e556dd25e445439635a185503a73ff2025-08-20T03:31:37ZengEDP SciencesITM Web of Conferences2271-20972025-01-01770102710.1051/itmconf/20257701027itmconf_emit2025_01027Analysis and research on the integration of education, technology and industry in smart educationShao Haiyan0Lv Jie1Sun Xuan2Wang Na3Wang Peng4Zhu Dongqing5Xue Hao6Chen Bin7Ma Yuzhen8School of Mechanical Engineering, University of Ji’nanSchool of Mechanical Engineering, University of Ji’nanSchool of Mechanical Engineering, University of Ji’nanSchool of Mechanical Engineering, University of Ji’nanSchool of Mechanical Engineering, University of Ji’nanSchool of Mechanical Engineering, University of Ji’nanSchool of Mechanical Engineering, University of Ji’nanShandong Youbaote Intelligent Robotics Co., Ltd.School of Mechanical Engineering, University of Ji’nanUnder the wave of digitalization and intelligence, smart education is becoming an important force to promote educational modernization, promote educational equity and improve educational quality. This manuscript elucidates the principle, features, and current progress of intelligent learning, with a particular emphasis on the examination of digital education strategies from different nations. From multiple dimensions, the differences between traditional education and smart education are compared and analyzed. The analysis examines the specific progression of intelligent education across different nations, emphasizing the fusion of educational and technological fields, the convergence between education and the industrial sector, and the tripartite integration of industry, academia, and research, along with the challenges. The focus of this manuscript is on pioneering integration strategies through case-based teaching, the joint educational framework of industry-academic convergence, the development of a multifaceted assessment approach, and the new ‘teacher-machine-student’ teaching model. The manuscript also discusses the future development trend of smart education. Research shows that the deep integration of smart education requires multi-party collaboration, continuous innovation of teaching models, further improvement of the evaluation system, and the fostering of creative individuals equipped for the demands of forthcoming societal challenges.https://www.itm-conferences.org/articles/itmconf/pdf/2025/08/itmconf_emit2025_01027.pdfsmart educationintegration of industryacademia and researchcase teachingdiversified evaluation system‘teacher-machine-student’ teaching modelartificial intelligence (ai)
spellingShingle Shao Haiyan
Lv Jie
Sun Xuan
Wang Na
Wang Peng
Zhu Dongqing
Xue Hao
Chen Bin
Ma Yuzhen
Analysis and research on the integration of education, technology and industry in smart education
ITM Web of Conferences
smart education
integration of industry
academia and research
case teaching
diversified evaluation system
‘teacher-machine-student’ teaching model
artificial intelligence (ai)
title Analysis and research on the integration of education, technology and industry in smart education
title_full Analysis and research on the integration of education, technology and industry in smart education
title_fullStr Analysis and research on the integration of education, technology and industry in smart education
title_full_unstemmed Analysis and research on the integration of education, technology and industry in smart education
title_short Analysis and research on the integration of education, technology and industry in smart education
title_sort analysis and research on the integration of education technology and industry in smart education
topic smart education
integration of industry
academia and research
case teaching
diversified evaluation system
‘teacher-machine-student’ teaching model
artificial intelligence (ai)
url https://www.itm-conferences.org/articles/itmconf/pdf/2025/08/itmconf_emit2025_01027.pdf
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