Learning-Related Sentiment Detection, Classification, and Application for a Quality Education Using Artificial Intelligence Techniques

作     者：Samah Alhazmi Shahnawaz Khan Mohammad Haider Syed 

作者机构：College of Computing and InformaticsSaudi Electronic UniversityRiyadh11673Saudi Arabia Country Bahrain PolytechnicIsa Town33349Bahrain 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第36卷第6期

页      面：3487-3499页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The authors extend their appreciation to the Deanship of Scientific Research at Saudi Electronic University for funding this research work through project number(8141) 

主　　题：Transfer learning AI modeling optimization sentiment analysis deep learning 

摘      要：Quality education is one of the primary objectives of any nation-build-ing strategy and is one of the seventeen Sustainable Development Goals(SDGs)by the United *** provide quality education,delivering top-quality con-tent is not ***,understanding the learners’emotions during the learning process is equally ***,most of this research work uses general data accessed from Twitter or other publicly available *** databases are generally not an ideal representation of the actual learning process and the learners’sentiments about the learning *** research has col-lected real data from the learners,mainly undergraduate university students of dif-ferent regions and *** analyzing the emotions of the students,appropriate steps can be suggested to improve the quality of education they *** order to understand the learning emotions,the XLNet technique is *** investigated the transfer learning method to adopt an efficient model for learners’sentiment detection and classification based on real *** experiment on the collected data shows that the proposed approach outperforms aspect enhanced sentiment analysis and topic sentiment analysis in the online learning community.