Data Mining and Analysis of NLP Methods in Students Evaluation of Teaching

被引:1
作者
Acosta-Ugalde, Diego [1 ]
Conant-Pablos, Santiago Enrique [1 ]
Camacho-Zuniga, Claudia [1 ]
Gutierrez-Rodriguez, Andres Eduardo [1 ]
机构
[1] Tecnol Monterrey, Escuela Ingn & Ciencias, Monterrey, NL, Mexico
来源
ADVANCES IN SOFT COMPUTING, MICAI 2023, PT II | 2024年 / 14392卷
关键词
NLP; Data Mining; Student Evaluation of Teaching; Education Rating; Machine Learning; Educational Innovation; QUALITY;
D O I
10.1007/978-3-031-47640-2_3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Student evaluations of teachings (SETs) are essential for determining the quality of the educational process. Natural Language Processing (NLP) techniques may produce informative insights into these surveys. This study aims to provide an overview of the various approaches used in NLP and sentiment analysis, focusing on identifying the top outcomes, models, and text representations used. Furthermore, we investigate NLP methods applied to a Spanish corpus of SETs, which is relatively uncommon, and discuss the application of less well-known tools in this scenario. In general, by showing the top models and text representations, especially in the case of a Spanish corpus, this study contributes to NLP and sentiment analysis. Additionally, it promotes research and interest in other languages that receive little attention.
引用
收藏
页码:28 / 38
页数:11
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