{"title":"Comparative Analysis of Cross-Cultural Teaching Management in Big Data Environment","authors":"Lihua Wang","doi":"10.3991/ijet.v18i11.41085","DOIUrl":null,"url":null,"abstract":"Cross-cultural teaching management in the big data environment not only enhances the quality and effectiveness of education but also promotes global cooperation and exchange in education, which has important practical significance and value. Existing methods for analyzing effectiveness and practicality are usually qualitative analysis methods. While this method emphasizes the complexity and diversity of educational phenomena, it may lead to subjectivity and instability in data processing and result presentation, affecting the reliability and objectivity of the analysis results. In this paper, a quantitative comparative analysis of the effectiveness and practicality of cross-cultural teaching management in the big data environment is conducted, which helps educators better understand the needs of students from different cultural backgrounds and develop more targeted teaching plans to improve the quality of education. First, the content of cross-cultural teaching management in the big data environment is explained, and the reasons and implementation process of the comparative analysis of effectiveness and practicality are provided. The evaluation indicators for the effectiveness and practicality of cross-cultural teaching management in the big data environment are determined, and the evaluation methods are given. Experimental analysis results are presented with examples to validate the effectiveness of the proposed method.","PeriodicalId":47933,"journal":{"name":"International Journal of Emerging Technologies in Learning","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Emerging Technologies in Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijet.v18i11.41085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Cross-cultural teaching management in the big data environment not only enhances the quality and effectiveness of education but also promotes global cooperation and exchange in education, which has important practical significance and value. Existing methods for analyzing effectiveness and practicality are usually qualitative analysis methods. While this method emphasizes the complexity and diversity of educational phenomena, it may lead to subjectivity and instability in data processing and result presentation, affecting the reliability and objectivity of the analysis results. In this paper, a quantitative comparative analysis of the effectiveness and practicality of cross-cultural teaching management in the big data environment is conducted, which helps educators better understand the needs of students from different cultural backgrounds and develop more targeted teaching plans to improve the quality of education. First, the content of cross-cultural teaching management in the big data environment is explained, and the reasons and implementation process of the comparative analysis of effectiveness and practicality are provided. The evaluation indicators for the effectiveness and practicality of cross-cultural teaching management in the big data environment are determined, and the evaluation methods are given. Experimental analysis results are presented with examples to validate the effectiveness of the proposed method.
期刊介绍:
This interdisciplinary journal focuses on the exchange of relevant trends and research results and presents practical experiences gained while developing and testing elements of technology enhanced learning. It bridges the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Fields of interest include, but are not limited to: -Software / Distributed Systems -Knowledge Management -Semantic Web -MashUp Technologies -Platforms and Content Authoring -New Learning Models and Applications -Pedagogical and Psychological Issues -Trust / Security -Internet Applications -Networked Tools -Mobile / wireless -Electronics -Visualisation -Bio- / Neuroinformatics -Language /Speech -Collaboration Tools / Collaborative Networks