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A Probe into the Mixed Teaching Design of College English Translation in the Era of Educational Big Data

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2020 International Conference on Applications and Techniques in Cyber Intelligence (ATCI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1244))

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Abstract

In the era of big data, through the analysis of educational data, find out the conditions that fit the students and teaching theory, so as to formulate more realistic educational teaching strategies. For this reason, this article brings up the research of college English translation mixed teaching in the era of educational big data. This paper designs a mixed teaching mode, and compares the traditional teaching mode with the mixed teaching mode of this article by setting up an experimental group and a control group. This study finds that the difference between the pre-teaching results of the experimental group and post-teaching is statistically significant (t = 9.270, P < 0.001), which proves that the mixed teaching mode has significantly improved the students’ English translation level, and their scores have improved significantly. The comparison between the control group score (80.04 ± 6.53) and the experimental group score (85.09 ± 6.33) was statistically significant (t = 4.263, P < 0.001), indicating that in the practical teaching research stage, the translation scores of the students in the control group and the experimental group were both It has improved, but the experimental group score is higher than the control group. The results of this paper provide reference value for the reform of the mixed teaching model of English translation in colleges and universities.

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Correspondence to Zhenhua Wei .

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Wei, Z. (2021). A Probe into the Mixed Teaching Design of College English Translation in the Era of Educational Big Data. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_126

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