How Can the Generative AI-Driven Intelligent Practical Teaching Model Enhance Teaching Effectiveness? -- Empirical Evidence from Accounting Majors in Colleges and Universities

Liangyan Lu; Kunyi Wang; Huimin Shao; Wanbao Yuan; Rui Zhao

doi:10.2991/978-2-38476-523-2_30

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How Can the Generative AI-Driven Intelligent Practical Teaching Model Enhance Teaching Effectiveness? -- Empirical Evidence from Accounting Majors in Colleges and Universities

Authors

Liangyan Lu¹, Kunyi Wang², Huimin Shao³^{, *}, Wanbao Yuan⁴, Rui Zhao⁵

¹Accounting and Finance Department, Yunnan College of Business Management, Kunming, Yunnan, 650500, China

²School of Economics, Yunnan Normal University, Kunming, Yunnan, 650500, China

³School of Management, Yunnan Normal University, Kunming, Yunnan, 650500, China

⁴School of Economics, Yunnan Normal University, Kunming, Yunnan, 650500, China

⁵Accounting and Finance Department, Yunnan College of Business Management, Kunming, China

^*Corresponding author. Email: 562859539@qq.com

Corresponding Author

Huimin Shao

Available Online 29 December 2025.

DOI: 10.2991/978-2-38476-523-2_30 How to use a DOI?
Keywords: AI 1; teaching effect 2; Human-Machine collaborative perception 3; Cognitive load 4
Abstract: Leveraging generative AI to enhance learning through effective teaching models is a central challenge in intelligent education research, which often remains at the technical application level, lacking insight into its internal mechanisms and boundary conditions. To address this gap, this study surveyed 109 students and employed hierarchical regression analysis. It systematically examines the direct effect of the teaching model, the mediating role of human-computer collaborative perception, and the moderating effect of cognitive load, thereby clarifying AI’s influence process. The findings offer a theoretical basis and practical path for educators to balance technological empowerment with cognitive load reduction.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 5th International Conference on New Media Development and Modernised Education (NMDME 2025)
Series: Advances in Social Science, Education and Humanities Research
Publication Date: 29 December 2025
ISBN: 978-2-38476-523-2
ISSN: 2352-5398
DOI: 10.2991/978-2-38476-523-2_30 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Liangyan Lu
AU  - Kunyi Wang
AU  - Huimin Shao
AU  - Wanbao Yuan
AU  - Rui Zhao
PY  - 2025
DA  - 2025/12/29
TI  - How Can the Generative AI-Driven Intelligent Practical Teaching Model Enhance Teaching Effectiveness? -- Empirical Evidence from Accounting Majors in Colleges and Universities
BT  - Proceedings of the 5th International Conference on New Media Development and Modernised Education (NMDME 2025)
PB  - Atlantis Press
SP  - 291
EP  - 298
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-523-2_30
DO  - 10.2991/978-2-38476-523-2_30
ID  - Lu2025
ER  -

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