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Evaluation of the Influence of Artificial Intelligence on College Students' Learning Based on Group Decision-making Method

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DOI: 10.23977/jaip.2023.060805 | Downloads: 58 | Views: 620

Author(s)

Jiaxiang Wang 1, Zongwen Tan 2, Fucai Zhou 1, Zhongwei Hu 3, Bingguang Fu 1, Yang Wang 1

Affiliation(s)

1 Southwest Jiaotong University Hope College, Chengdu, Sichuan, China
2 Sichuan Police College, Luzhou, Sichuan, China
3 Southwest University, Chongqing, China

Corresponding Author

Jiaxiang Wang

ABSTRACT

The rapid development of artificial intelligence technology is transforming people's lifestyles and work patterns across various fields. In the realm of education, it also exerts an influence on the learning experiences of university students. To comprehend the multifaceted impact of artificial intelligence on university students' learning, this paper collected feedback results from a survey on artificial intelligence. Through statistical analysis and differentiation of survey data, focusing on prioritization, scientificity, operability, and rationality, we identified several evaluation indicators that best reflect the impact of artificial intelligence on university students in this survey. Subsequently, by establishing models based on the data and considering the weights and impact levels of different indicators, we utilized group decision methods to quantitatively assess the most crucial aspects of the influence of artificial intelligence on university students' learning. The analysis results provide a comprehensive evaluation of the potential impact of artificial intelligence learning tools on university students' learning.

KEYWORDS

Artificial Intelligence, Mathematical Evaluation Model, Group Decision Methods, Analytic Hierarchy Process

CITE THIS PAPER

Jiaxiang Wang, Zongwen Tan, Fucai Zhou, Zhongwei Hu, Bingguang Fu, Yang Wang, Evaluation of the Influence of Artificial Intelligence on College Students' Learning Based on Group Decision-making Method. Journal of Artificial Intelligence Practice (2023) Vol. 6: 26-34. DOI: http://dx.doi.org/10.23977/jaip.2023.060805.

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