Conference paper Gold Open Access 2025

Empirical study on the influencing factors of improving the teaching ability of green energy economics based on digital twin technology

Proceedings of 2025 8th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2025
Conference · pp. 1058-1065
Abstract

How to enhance the teaching ability of green energy economics from the perspective of industry education integration and rely on digital twin technology has become a key issue in breaking through the bottleneck of higher education development research. This study used data from Chinese higher education institutions from 2010 to 2024 as samples, and verified the impact and mechanism of industry education integration on the teaching ability of green energy economics through a multi period double difference model. The results indicate that the integration of industry and education can significantly enhance the teaching ability of green energy economics; The integration of industry and education can be achieved through the development and application of effective digital teaching tools for energy economy. Its core path includes utilizing digital twins and IoT technology to optimize the construction of virtual simulation teaching scenarios, realizing dynamic simulation of complex scenarios such as the economic operation of wind and solar power plants, thereby promoting the improvement of teaching capabilities in green energy economics; The integration of industry and education can be achieved by optimizing the construction of virtual simulation teaching scenarios, relying on Python, machine learning algorithms, and blockchain technology to promote the development and application of digital teaching tools for energy economics (such as intelligent energy cost calculation systems and distributed energy trading simulation platforms), ultimately promoting the improvement of teaching capabilities in green energy economics,. Based on this, it is recommended to deepen the collaboration between schools and enterprises in technology (jointly developing digital courses and algorithm tools), optimize teaching processes (integrating big data analysis and AI policy simulation training), establish a digital tool iteration mechanism, and improve the computing resource guarantee system, in order to leverage the collaborative empowerment of industry education integration and computer technology. © 2025 Copyright held by the owner/author(s).

Keywords

Author Keywords

Energy economy Green energy Industry education integration Teaching ability Virtual simulation

Index Keywords

E-learning Learning systems Teaching Engineering education Education computing Machine learning Learning algorithms Virtual reality Big data Digital twin Economic analysis Energy economics Energy policy Green computing Green development Green economy Industrial economics Integration Simulation platform Development and applications Digital teachings Energy economy Green energy Industry education integration Simulation teachings Teaching ability Teaching tools Virtual simulations Solar energy
Author Affiliations
Panzhihua University, Panzhihua, Sichuan, China
School of Economics and Management, Panzhihua University, Panzhihua, Sichuan, China
Funding & Acknowledgements
Grant: 2412315535
Thank you for the funding of the collaborative education project between industry and academia. The title of this project is \"Energy Economy Teaching Capacity Enhancement Project under the Background of Green Energy and Sustainable Development\": 2412315535.
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