Artificial Intelligence Empowerment in Teacher Training for Innovation and Entrepreneurship Education: A Theoretical Framework and Technical Pathways

This paper explores the application of artificial intelligence (AI) technologies in enhancing teacher training for innovation and entrepreneurship education in higher education. By integrating the theoretical framework and technical approaches, this study provides solutions to the problems such as insufficient personalization and lack of practical experience existing in the traditional teacher training model, and proposes methods such as constructing intelligent teacher capability archives, intelligent resource recommendations, and virtual practice scenarios.These innovations aim to improve the precision, personalization, and practicality of teacher training. The paper further discusses the technical infrastructure required for AI integration and highlights ethical considerations, such as data security and algorithmic fairness. This work contributes to the development of a sustainable and adaptive teacher training ecosystem in the AI era.

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Publication Details

Journal
Global Humanities and Social Sciences
Published
2025-08-25
DOI
https://doi.org/10.61360/bonighss252018510507
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence Empowerment in Teacher Training for Innovation and Entrepreneurship Education: A Theoretical Framework and Technical Pathways

Wei Hu, Peiqing Yao
Global Humanities and Social Sciences
Technology-Enhanced Education Studies
article

Artificial Intelligence Empowerment in Teacher Training for Innovation and Entrepreneurship Education: A Theoretical Framework and Technical Pathways

Wei Hu, Peiqing Yao
article en

Abstract

This paper explores the application of artificial intelligence (AI) technologies in enhancing teacher training for innovation and entrepreneurship education in higher education. By integrating the theoretical framework and technical approaches, this study provides solutions to the problems such as insufficient personalization and lack of practical experience existing in the traditional teacher training model, and proposes methods such as constructing intelligent teacher capability archives, intelligent resource recommendations, and virtual practice scenarios.These innovations aim to improve the precision, personalization, and practicality of teacher training. The paper further discusses the technical infrastructure required for AI integration and highlights ethical considerations, such as data security and algorithmic fairness. This work contributes to the development of a sustainable and adaptive teacher training ecosystem in the AI era.

Global Humanities and Social SciencesVol. 6(5)
Jiaxing University (CN)
Openalex Percentile: Top 74%
Technology-Enhanced Education Studies
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