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Application of AHP Algorithm Based on Data Mining in Higher Education Teaching Evaluation System

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Frontier Computing on Industrial Applications Volume 3 (FC 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1133))

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Abstract

The higher education teaching evaluation is receiving increasing attention. AHP (Analytic Hierarchy Process) is a multi domain and multi-level analysis method for decision-making problems, which is also widely used in higher education teaching evaluation. This article proposes a higher education teaching evaluation. The system is evaluated based on multiple indicators such as students’ academic performance, teachers’ teaching abilities, teaching environment, and teaching facilities. DM algorithm is used to mine data, and AHP algorithm is used to perform hierarchical analysis and weight calculation on indicators. The experimental results indicate that the system can provide useful information and decision support for higher education teaching evaluation.

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References

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Authors and Affiliations

  1. Anhui Xinhua University, Hefei, 230088, Anhui, China

    Miaomiao Xu

Authors
  1. Miaomiao Xu
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Correspondence to Miaomiao Xu .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung City, Taiwan

    Jason C. Hung

  2. School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu, Japan

    Neil Yen

  3. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung City, Taiwan

    Jia-Wei Chang

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Xu, M. (2024). Application of AHP Algorithm Based on Data Mining in Higher Education Teaching Evaluation System. In: Hung, J.C., Yen, N., Chang, JW. (eds) Frontier Computing on Industrial Applications Volume 3. FC 2023. Lecture Notes in Electrical Engineering, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-99-9416-8_7

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  • DOI: https://doi.org/10.1007/978-981-99-9416-8_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9415-1

  • Online ISBN: 978-981-99-9416-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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