Optimization Strategy of Teaching Resources Based on Artificial Intelligence

Author Names:
Xiaoxia Ye, Xiaohong Peng
Author Affiliation:
College of Mathematics and Computer, Guangdong Ocean University, Zhanjiang, China
Author Email:
xiaohong_peng@outlook.com
Publication Date:
April 24, 2026

Page numbers:

DOI Number:

https://doi.org/10.66113/jcmse.26.142

Abstract:

With the rapid development and wide application of artificial intelligence (AI) technology in the field of education, this study aims to explore and evaluate the application strategies of AI in the optimization of teaching resources. Using a combination of questionnaires, data analysis, and machine learning models, the study provides an in-depth analysis of the possibilities and practical effects of AI in optimizing teaching resources. The questionnaire collected the attitudes and use of AI teaching resources by educators and students, and the random forest model was used to evaluate the effectiveness of AI in optimizing teaching resources. The results show that educators and students generally agree that AI can significantly improve teaching quality and meet personalized learning needs. However, the study also reveals data sample bias and limitations in the model’s ability to generalize. Overall, this study provides an empirical basis for understanding the potential of AI in the optimization of educational resources, while pointing to the direction of future research
Keywords:
Artificial intelligence; Teaching resource optimization strategy; Machine learning; Educational technology
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