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Prediction and Early Warning of the Teaching Process Based on CMM Model

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Proceedings of the 2012 International Conference on Information Technology and Software Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 211))

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Abstract

In this paper, we proposed to apply CMM model in the teaching process, based on analysis of the CMM model. Established a prediction model and warning model, and to directions the feasibility and reliability of the model, combine with the actual data. The results show that colleges and universities to establish the teaching process of CMM-based forecasting and early warning model is feasible, and help colleges and universities to complete the teaching work more scientific, rational and effective use of existing resources.

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Author information

Authors and Affiliations

  1. Information Engineering Institute, Capital Normal University, No. 56 North Road, 3rd Ring Road West, Haidian District, 100048, Beijing, China

    Hua Wang, Ningning Chen & Jing Chen

Authors
  1. Hua Wang
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  2. Ningning Chen
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  3. Jing Chen
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Corresponding author

Correspondence to Jing Chen .

Editor information

Editors and Affiliations

  1. Beijing Jiaotong University, Beijing, China, People's Republic

    Wei Lu

  2. Beijing Jiaotong University, Beijing, China, People's Republic

    Guoqiang Cai

  3. Beijing Jiaotong University, Beijing, China, People's Republic

    Weibin Liu

  4. Beijing Jiaotong University, Beijing, China, People's Republic

    Weiwei Xing

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Cite this paper

Wang, H., Chen, N., Chen, J. (2013). Prediction and Early Warning of the Teaching Process Based on CMM Model. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34522-7_22

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  • DOI: https://doi.org/10.1007/978-3-642-34522-7_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34521-0

  • Online ISBN: 978-3-642-34522-7

  • eBook Packages: EngineeringEngineering (R0)

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