{"title":"Intelligent Learning Platform with Deep Neural Network for Korean Language Teaching in Universities","authors":"Yuwen Zhang","doi":"10.5750/ijme.v1i1.1411","DOIUrl":null,"url":null,"abstract":"Intelligent learning represents a dynamic approach to education that provides innovative technologies and personalized methodologies to enhance learning outcomes. Intelligent teaching adapts instruction to the individual needs, preferences, and progress of each student. This approach enables educators to tailor curriculum delivery, identify areas for improvement, and provide timely feedback, fostering a more engaging and effective learning environment. Moreover, intelligent teaching promotes collaborative learning experiences and encourages critical thinking skills, preparing students for success in an increasingly digital and interconnected world. This paper proposed a framework of Generative Platform-Oriented Intelligent Deep Neural Network (GPoIDNN) for Korean language teaching in Universities. The proposed GPoIDNN network comprises a social media platform for the promotion of Korean language teaching among students. With the GPoIDNN platform, a Generative network is implemented for the analysis of the factors involved in Language teaching in universities. The platform considered for the proposed model is Weibo for acquiring in-depth information about the language learning process. Upon the estimated features GPoIDNN uses the Generative Deep Neural Network platform for the classification and examination of the student performance. With the Weibo platform in social media, the Generative network constructs the intelligent teaching system for the Korean language teaching process in University students. The examination of student performance demonstrated that the proposed GPoIDNN model improves the student learning of Korean language with improved by 73% through the intelligent model. Further, the keywords and opinions classified with the GPoIDNN model exhibits a higher classification rate of 0.98 based on the opinion of the students in the universities.","PeriodicalId":50313,"journal":{"name":"International Journal of Maritime Engineering","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Maritime Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.5750/ijme.v1i1.1411","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MARINE","Score":null,"Total":0}
引用次数: 0
Abstract
Intelligent learning represents a dynamic approach to education that provides innovative technologies and personalized methodologies to enhance learning outcomes. Intelligent teaching adapts instruction to the individual needs, preferences, and progress of each student. This approach enables educators to tailor curriculum delivery, identify areas for improvement, and provide timely feedback, fostering a more engaging and effective learning environment. Moreover, intelligent teaching promotes collaborative learning experiences and encourages critical thinking skills, preparing students for success in an increasingly digital and interconnected world. This paper proposed a framework of Generative Platform-Oriented Intelligent Deep Neural Network (GPoIDNN) for Korean language teaching in Universities. The proposed GPoIDNN network comprises a social media platform for the promotion of Korean language teaching among students. With the GPoIDNN platform, a Generative network is implemented for the analysis of the factors involved in Language teaching in universities. The platform considered for the proposed model is Weibo for acquiring in-depth information about the language learning process. Upon the estimated features GPoIDNN uses the Generative Deep Neural Network platform for the classification and examination of the student performance. With the Weibo platform in social media, the Generative network constructs the intelligent teaching system for the Korean language teaching process in University students. The examination of student performance demonstrated that the proposed GPoIDNN model improves the student learning of Korean language with improved by 73% through the intelligent model. Further, the keywords and opinions classified with the GPoIDNN model exhibits a higher classification rate of 0.98 based on the opinion of the students in the universities.
期刊介绍:
The International Journal of Maritime Engineering (IJME) provides a forum for the reporting and discussion on technical and scientific issues associated with the design and construction of commercial marine vessels . Contributions in the form of papers and notes, together with discussion on published papers are welcomed.