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Research on Improving Education Quality and Efficiency through Artificial Intelligence and Big Data Analysis

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DOI: 10.23977/jaip.2023.060806 | Downloads: 17 | Views: 477

Author(s)

Junting Nie 1

Affiliation(s)

1 Xinyang Vocational and Technical College, Xinyang, Henan, 464000, China

Corresponding Author

Junting Nie

ABSTRACT

This study mainly focuses on using artificial intelligence and big data analysis technology to improve the quality and efficiency of education. Firstly, we introduced the basic concepts and development history of artificial intelligence and big data analysis, and outlined their current application status in the field of education. Then, the advantages and challenges of artificial intelligence and big data analysis in improving education quality and efficiency were discussed. Next, the integration application of artificial intelligence and big data analysis was explored, and practical cases in the field of education were provided. We discussed in detail the specific methods and applications of using artificial intelligence and big data analysis to improve education quality and efficiency, including the construction and optimization of personalized teaching models, prediction and intervention of student learning behavior, and the development and application of teacher assistance tools. Finally, the main conclusions of the study were summarized, the limitations of the study were pointed out, and suggestions were made for future research directions and development in the field of education. Through this study, it is hoped that it can provide reference and guidance for research on using artificial intelligence and big data analysis to improve education quality and efficiency. 

KEYWORDS

Artificial intelligence, big data analysis, education quality, education efficiency, personalized teaching

CITE THIS PAPER

Junting Nie, Research on Improving Education Quality and Efficiency through Artificial Intelligence and Big Data Analysis. Journal of Artificial Intelligence Practice (2023) Vol. 6: 35-40. DOI: http://dx.doi.org/10.23977/jaip.2023.060806.

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