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International Journal of New Developments in Education, 2025, 7(6); doi: 10.25236/IJNDE.2025.070609.

AI-Enabled Teaching Reform in Public Administration: Diverse Pathways and Practices for Risk Management Course

Author(s)

Cuizhen Xia1, Xiaojun Luo1

Corresponding Author:
Cuizhen Xia
Affiliation(s)

1School of Politics and Public Administration, Guangxi Normal University, Guilin, China

Abstract

In the context of the rapid development of artificial intelligence(AI), exploring the diverse pathways for integrating AI into the teaching of risk management courses in public administration is of positive significance for cultivating high-quality public risk managers adapted to the current complex risk environment. This research reflects on the existing problems in traditional teaching models and analyzes the theoretical and practical foundations of AI-enabled teaching reforms. By leveraging a multi-platform AI toolkit and the Rain Classroom hybrid teaching platform, a course reform plan is proposed, which includes intelligent learning situation analysis, dynamic updates of teaching content, interactive classroom teaching, and intelligent evaluation system. Practical verification has demonstrated that this plan effectively enhances students' learning interest, knowledge application capabilities, and practical operation skills. However, although the effect of AI-enabled teaching is obvious in the short term, its long-term use may also lead to problems such as thinking dependence, misinformation and academic misconduct. It is necessary to continuously track the effect of AI-enabled teaching and adopt adaptive teaching strategies to utilize its advantages and reduce the negative impact.

Keywords

Artificial Intelligence; Risk Management; Teaching Reform; AI-Enabled Teaching

Cite This Paper

Cuizhen Xia, Xiaojun Luo. AI-Enabled Teaching Reform in Public Administration: Diverse Pathways and Practices for Risk Management Course. International Journal of New Developments in Education (2025), Vol. 7, Issue 6: 60-65. https://doi.org/10.25236/IJNDE.2025.070609.

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