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Construction of English Multimodal Classroom in Colleges and Universities Under Big Data Environment

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Data and Information in Online Environments (DIONE 2021)

Abstract

With the multi-modality of college foreign language cognitive style and dimensions, China's higher education curriculum reform also has higher requirements for the traditional class teaching system based on practice. It is of great urgency and necessity for teachers to establish effective teaching concepts and guide classroom teaching to realize effective teaching. Under the background of big data, the current traditional British teaching mode does not meet the application requirements of independent colleges. Massive open online course and microteaching have become trends in the field of education. The introduction of multi-modal discourse analysis theory brings new ideas, methods and teaching design to English teaching. College English takes classroom teaching as the main body, and the collaborative application of multi-modal discourse changes the rigid explanation mode. Based on the analysis of the integration of big data and multimodality in the current college English curriculum, this paper has initially formed a theoretical framework for the construction and evaluation of multimodal classroom environment in China. Teachers need to use their rich working experience and profound knowledge to create a good learning atmosphere for students.

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Ma, L. (2021). Construction of English Multimodal Classroom in Colleges and Universities Under Big Data Environment. In: Bisset Álvarez, E. (eds) Data and Information in Online Environments. DIONE 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-030-77417-2_35

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  • DOI: https://doi.org/10.1007/978-3-030-77417-2_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77416-5

  • Online ISBN: 978-3-030-77417-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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