Research on the Construction of a Multi-dimensional Evaluation System for Industry-Education Integration in Higher Vocational Education Empowered by Artificial Intelligence

Gangnian Xu; Yingke Wang; Zihan Li; Yizhuo Zheng; Xinhong Shi

doi:10.6918/

Authors

Gangnian Xu School of Civil Engineering, Shandong Jiaotong University, Jinan 250357, China
Yingke Wang School of Civil Engineering, Shandong Jiaotong University, Jinan 250357, China
Zihan Li School of Civil Engineering, Shandong Jiaotong University, Jinan 250357, China
Yizhuo Zheng School of Civil Engineering, Shandong Jiaotong University, Jinan 250357, China
Xinhong Shi School of Civil Engineering, Shandong Jiaotong University, Jinan 250357, China

DOI:

https://doi.org/10.6918/

Keywords:

Artificial Intelligence, Higher Vocational Education, Industry-Education Integration, Intelligent Evaluation.

Abstract

Due to the fast growth of artificial intelligence, big data, and other emerging digital technologies, the interaction between industry and education in higher vocational education is experiencing changes towards digitalization and intelligence. A good evaluation system is necessary to enhance the quality of industry-education integration and enhance the extensive cooperation between vocational colleges and enterprises. Nevertheless, the modern methods of evaluation are confronted with issues like low involvement of many stakeholders, lack of criteria, narrow use of data resources and poor dynamics of feedback. There are previous researches which can prove that industry-education integration evaluation should be a systematic framework involving several dimensions, such as cooperation foundation, implementation process, and development effectiveness. At the same time, multi-source data fusion and intelligent evaluation systems offer different tools to enhance vocational education evaluation systems. The authors discuss the issues in the evaluation of industry-education integration in higher vocational education and suggest the artificial intelligence-based multi-dimensional evaluation system by utilizing multi-source data integration, multi-stakeholders collaboration, and optimizing the intelligent feedback. The given strategy will help facilitate the change in the evaluation of the experience-based assessment to data-driven decision-making and give theoretical support and practical solutions to enhance the quality of higher vocational education.

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