Abstract
This paper identifies the characteristics of anomie behaviors of MOOC learners through the cluster analysis of those anomie behaviors, and finds out the initial paths of intelligent recognition through online analysis of the background data characteristics of these anomie behaviors. The paper also suggests that these identification paths are not difficult to find, but there are still some profound reasons why many MOOC companies have not adopted those paths so far.
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Acknowledgments
The paper is supported by the foundation of Fujian Province Educational Science “Thirteenth Five-Year Plan” 2018 Project—“Research on the college students’ anomie of online courses learning and intervention of their online courses learning” (No. FJJKCGZ18-850, Key funding project), Young and Middle-aged Teacher Educational and Scientific Research Project of Fujian Province—“Research on the college students’ anomie of online courses learning and intervention of their online courses learning”, and the Teaching Reform Research Project of Minjiang University in 2018—“The Interventional Teaching Reform aimed at the online courses learning anomie of college students” (No. MJU2018A005).
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Shutang Liu drafts the whole article, and accepts direct responsibility for the manuscript.
Fuquan Zhang proposed the first step of the paper proposal, and contributes the conception of intelligent recognition, and gives the direction and suggestion for revising the article critically.
Chunfen Jiang revises the translation of the paper, and is responsible for the language of the paper.
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Liu, S., Zhang, F., Jiang, C. (2019). Preliminary Ideas for Intelligent Recognition Paths of Anomie Behaviors Among MOOC Learners. In: Zhao, Y., Wu, TY., Chang, TH., Pan, JS., Jain, L. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. VTCA 2018. Smart Innovation, Systems and Technologies, vol 128. Springer, Cham. https://doi.org/10.1007/978-3-030-04585-2_22
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DOI: https://doi.org/10.1007/978-3-030-04585-2_22
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