Evaluation Analysis on Influences of AHP-TOPSIS-Model-Based Artificial Intelligence on College Students Learning
DOI:
https://doi.org/10.54097/qm2t3431Keywords:
Artificial Intelligence, College Student Learning, Evaluation Analysis, AHP-TOPSIS Model.Abstract
In recent years, the field of artificial intelligence has witnessed rapid development and continuous technological advancements. It has found widespread application in various domains, exerting profound influences on all aspects of human social life. This article focuses on evaluating the impact of artificial intelligence on college students' learning. Based on a survey of 4605 participants, the collected data was transformed into numerical values and underwent preliminary data processing. An indicator evaluation system was established, encompassing priority, scientificity, and feasibility, in order to construct a comprehensive evaluation framework. By conducting both objective and subjective analyses of the survey questions, the obtained weight values were subjected to consistency tests, which confirmed their reliability. Through the application of the Analytic Hierarchy Process (AHP), the final weights were determined, and the top eight indicators were selected for evaluation. An AHP-TOPSIS combined evaluation model was developed, which concludes that artificial intelligence has significantly influenced college students' learning and yielded positive effects. The novelty of this article lies in the utilization of the AHP-TOPSIS combined evaluation model, which incorporates the advantages of both models and avoids the limitations associated with a single model, such as biased perspectives and low reliability.
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