Comparative Analysis of Cross-Cultural Teaching Management in Big Data Environment

Q1 Social Sciences
Lihua Wang
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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.
大数据环境下跨文化教学管理的比较分析
大数据环境下的跨文化教学管理不仅提高了教育的质量和有效性,而且促进了全球教育合作与交流,具有重要的现实意义和价值。现有的分析有效性和实用性的方法通常是定性分析方法。这种方法虽然强调教育现象的复杂性和多样性,但可能导致数据处理和结果呈现的主观性和不稳定性,影响分析结果的可靠性和客观性。本文对大数据环境下跨文化教学管理的有效性和实用性进行了定量比较分析,有助于教育工作者更好地了解不同文化背景学生的需求,制定更有针对性的教学计划,以提高教育质量。首先,阐述了大数据环境下跨文化教学管理的内容,并提供了有效性和实用性比较分析的原因和实施过程。确定了大数据环境下跨文化教学管理有效性和实用性的评价指标,并给出了评价方法。实验分析结果与算例验证了该方法的有效性。
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来源期刊
自引率
0.00%
发文量
352
审稿时长
12 weeks
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
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