Starting from the Comprehensive Evaluation Results of Shanghai Secondary Vocational School Students: Exploring the Quantitative Path of Educational Text Evaluation with the Aid of Artificial Intelligence
Year: 2025
Type: conference-paper
Abstract: Although text analysis is used as a popular tool in big data, such as public opinion analysis, service evaluation, there is a lack of sufficient application cases in educational evaluation. Based on the data of the comprehensive quality evaluation of students from 18 secondary vocational schools in Shanghai, this paper uses a dictionary-based sentiment analysis method to propose a quantitative path of education text evaluation. By combining the analysis results of Baidu AI, the dictionary is improved and the results are adjusted. A Python program is written for sentiment analysis and statistical calculations. This paper proposes a quantitative solution for text evaluation, provides final scores and ranking suggestions for a given dataset, enabling the effective utilization of teachers' evaluations text. It has certain reference significance for researchers in the fields of big data, artificial intelligence, and education.
Authors: Xianglan Gao, Kejun Wei
Institution: Shanghai Lida University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4413812535