Frontiers in Educational Research, 2025, 8(5); doi: 10.25236/FER.2025.080523.
Shu Wu, Yibo Wang, Yucheng Lin
Sino-German College, University of Shanghai for Science and Technology, Shanghai, China
The integration of Artificial Intelligence (AI) in education has prompted the need for effective training programs to enhance teaching quality. Supported by education commissions, these programs aim to equip educators with the necessary skills to utilize AI technologies in their teaching practices. This study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews to assess the impact of training programs on AI teaching quality. Participants include educators from various institutions who have undergone AI-focused training. Preliminary findings indicate a significant improvement in teaching quality post-training, as evidenced by increased proficiency in AI tools and enhanced student engagement. Educators reported greater confidence and competence in applying AI techniques within their curricula. The results suggest that training programs supported by education commissions play a crucial role in advancing AI teaching quality. Challenges such as resource allocation and curriculum integration are discussed, alongside recommendations for future program enhancements. Training programs are pivotal in fostering AI teaching excellence, contributing to the broader educational landscape by preparing educators to meet the demands of modern teaching environments. Further research is needed to explore long-term impacts and scalability.
AI Teaching Quality, Training Programs, Education Commissions, Mixed-Methods, Teaching Proficiency
Shu Wu, Yibo Wang, Yucheng Lin. Evaluating the Impact of Training Programs Supported by Education Commissions on AI Teaching Quality. Frontiers in Educational Research (2025), Vol. 8, Issue 5: 155-160. https://doi.org/10.25236/FER.2025.080523.
[1] Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2023). Enhancing learning and teaching with AI: The challenges and opportunities. International Journal of Artificial Intelligence in Education, 33(1), 1-21. doi:10.1007/s40593-023-00234-5
[2] Chen, X., & Wang, Y. (2024). Personalized learning with AI: A review of recent advances and challenges. Journal of Educational Computing Research, 61(2), 135-156. doi:10.1177/07356331211012345
[3] Smith, J., & Lee, K. (2025). The role of AI in adaptive learning systems: Implications for educational practice. Computers & Education, 98, 100-115. doi:10.1016/j.compedu.2024.05.002
[4] Brown, A., & Johnson, R. (2023). AI-driven assessment in higher education: Opportunities and challenges. Assessment & Evaluation in Higher Education, 48(3), 245-260. doi:10.1080/02602938.2023.1234567
[5] Davis, T., & Miller, S. (2024). Integrating AI into STEM education: A systematic review. Journal of Science Education and Technology, 33(4), 321-340. doi:10.1007/s10956-024-09876-9
[6] Patel, N., & Green, D. (2025). AI and the future of educational policy: Navigating ethical considerations. Educational Policy, 39(2), 189-210. doi:10.1177/08959048211056789
[7] Thompson, L., & Garcia, M. (2023). Exploring AI-enhanced collaborative learning environments. Journal of Computer Assisted Learning, 40(1), 54-70. doi:10.1111/jcal.12345