Analysis and Prediction of the Trend Features for Teaching Development Based on Knowledge Discovery

Authors

  • Peng Su
  • Yan Wang
  • Ping Zhao
  • Mingli Gao
  • Xiwen Liu
  • Guiling Liu
  • Changtian Wang

DOI:

https://doi.org/10.3991/ijet.v17i05.29845

Keywords:

knowledge discovery, college teachers, teaching development, trend feature analysis, trend prediction

Abstract


The existing research on teaching development of teachers fails to effectively quantify the teaching development trend. This paper deeply mines the evaluation data on the teaching quality of college teachers, before analyzing and predicting the trend features for teaching development of college teachers based on knowledge discovery. Firstly, the knowledge features of the teaching development trend of college teachers were examined. Next, the fluctuation features of the time series on the teaching quality development of college teachers were described based on chaotic time series. In addition, a prediction model for teaching development of college teachers was established for weighted first-order chaotic time series, and used to simulate the nonlinear features of the time series on the teaching quality development of college teachers. The prediction model was proved effective through experiments.

Cover iJET Vol. 17 No. 05 (2022)

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Published

2022-03-14

How to Cite

Su, P. ., Wang, Y. ., Zhao, P. ., Gao, M. ., Liu, X. ., Liu, G. ., & Wang, C. . (2022). Analysis and Prediction of the Trend Features for Teaching Development Based on Knowledge Discovery. International Journal of Emerging Technologies in Learning (iJET), 17(05), pp. 120–132. https://doi.org/10.3991/ijet.v17i05.29845

Issue

Vol. 17 No. 05 (2022)

Section

Papers

License

Copyright (c) 2022 Nan Zhang (Submitter); Peng Su, Yan Wang, Ping Zhao, Mingli Gao, Xiwen Liu, Guiling Liu, Changtian Wang

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