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A Study on Non-english Majors’ Cognitive Adaptation and Learning Performance in Flipped Classroom

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Blended Learning: Aligning Theory with Practices (ICBL 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9757))

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Abstract

This paper, using a mixed method, designed the college English Flipped Classroom from the perspective of curriculum, and examined the students’ cognitive adaptation, engagement and application skills. It was found that the students differed in cognitive adaption (students good at listening and speaking performed better), and their listening and speaking were improved. Moreover, speaking significantly correlated with in-class interaction and group collaboration. Finally, it was suggested that based on the level of speaking and listening, stratified teaching could be carried out to provide pre-class, in-class and post-class facilitation respectively.

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Acknowledgement

This research was supported in part by a grant from the Grant Program: Study on the resource, model and evaluation of mobile learning in promoting rural Minority education justice in Yunnan Province of China (JD2014YB10), Research on the application of MOOC in Chinese rural weak schools from the perspective of equity (2015M581763) and Localization sharing and blended learning model of rural MOOCs (2016YB139) funded by “Online Educational Fund of Chinese Education Ministry online education research centre”

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Correspondence to Xiaoyan Qiao .

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© 2016 Springer International Publishing Switzerland

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Zhou, Y., Qiao, X., Zhang, H. (2016). A Study on Non-english Majors’ Cognitive Adaptation and Learning Performance in Flipped Classroom. In: Cheung, S., Kwok, Lf., Shang, J., Wang, A., Kwan, R. (eds) Blended Learning: Aligning Theory with Practices . ICBL 2016. Lecture Notes in Computer Science(), vol 9757. Springer, Cham. https://doi.org/10.1007/978-3-319-41165-1_16

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  • DOI: https://doi.org/10.1007/978-3-319-41165-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41164-4

  • Online ISBN: 978-3-319-41165-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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