Integration of Intelligent Generation and Education: Research and Practice of AIGC Driven Intelligent Teaching Resources in Universities

With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, the education sector is undergoing profound changes. This article explores the application of AIGC technology in the production of smart teaching resources in universities, aiming to improve the efficiency and quality of teaching resource production through intelligent generation technology. AIGC technology has the characteristics of multimodal generation capability, efficiency, and intelligence. It can automatically generate teaching scripts, virtual teacher images, graphic materials, and other content, significantly shortening the production cycle and reducing production costs. This article proposes an AIGC driven framework for intelligent teaching resource production, which includes core modules such as teaching content generation, virtual teacher generation, and video production. The production process of virtual teacher intelligent teaching resources is demonstrated through practical cases. Practice has shown that AIGC technology has greatly improved the efficiency of teaching resource production, and the participation and satisfaction of learners have significantly increased. However, the quality of AIGC generated content and the interactivity of virtual teachers still need further optimization. In the future, with the continuous development of AIGC technology, the production of intelligent teaching resources for virtual teachers will become more intelligent and personalized, bringing more innovation and change to the field of education.

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Published
2025-04-18
DOI
https://doi.org/10.1109/cste64638.2025.11092085
Primary Topic
Big Data Technologies and Applications
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article
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article

Integration of Intelligent Generation and Education: Research and Practice of AIGC Driven Intelligent Teaching Resources in Universities

Xin Xie, Xiaoli Yang, Rongyu Cui
Big Data Technologies and Applications
article

Integration of Intelligent Generation and Education: Research and Practice of AIGC Driven Intelligent Teaching Resources in Universities

Xin Xie, Xiaoli Yang, Rongyu Cui
article en

Abstract

With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, the education sector is undergoing profound changes. This article explores the application of AIGC technology in the production of smart teaching resources in universities, aiming to improve the efficiency and quality of teaching resource production through intelligent generation technology. AIGC technology has the characteristics of multimodal generation capability, efficiency, and intelligence. It can automatically generate teaching scripts, virtual teacher images, graphic materials, and other content, significantly shortening the production cycle and reducing production costs. This article proposes an AIGC driven framework for intelligent teaching resource production, which includes core modules such as teaching content generation, virtual teacher generation, and video production. The production process of virtual teacher intelligent teaching resources is demonstrated through practical cases. Practice has shown that AIGC technology has greatly improved the efficiency of teaching resource production, and the participation and satisfaction of learners have significantly increased. However, the quality of AIGC generated content and the interactivity of virtual teachers still need further optimization. In the future, with the continuous development of AIGC technology, the production of intelligent teaching resources for virtual teachers will become more intelligent and personalized, bringing more innovation and change to the field of education.

Chengdu University (CN)
Quality Education
Openalex Percentile: Top 80%
Big Data Technologies and Applications
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Integration of Intelligent Generation and Education: Research and Practice of AIGC Driven Intelligent Teaching Resources in Universities — Xin Xie, Xiaoli Yang, et al. · (2025) | TGRS Research Map | TGRS