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Research on the Construction of a Data Warehouse Model for College Student Performance

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Data Science (ICPCSEE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1880))

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Abstract

Students’ grades not only serve as an effective indicator of their learning achievements but also to some extent reflect the completion of teaching tasks by the instructors. Currently, many universities across the country have collected and recorded various information about students and teachers in the school’s information management system, but it is only a simple storage record and has not effectively excavated hidden information, and data have not been fully utilized. Student performance information, enrolment information, course information, teaching plans, and teacher-related information are currently stored in separate databases, which are independent of each other, making it difficult to perform effective data analysis . Data warehousing technology can integrate various information and use data analysis software to excavate more high-value information, which is convenient for teaching evaluation and optimizing teaching strategies. Based on data warehousing technology, the article uses the hierarchical concept of data warehousing to construct the ODS layer, DWD layer, DWS layer and ETL layer. Facing the data warehousing topic, the article designs the data warehousing conceptual model, logical model, and physical model based on student performance, providing a model basis for later data mining.

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References

  1. Deng, J., Mei, Y.: Clustering analysis of achievement early warning based on behavior data of college students. Mod. Inf. Technol. 7(6), 35–38 (2023)

    Google Scholar 

  2. Li, F., Xu, H., et al.: Research on the integration of university academic information data based on data mining and K-means algorithm. J. Heilongjiang Inst. Technol. 36(4), 31–36 (2023)

    Google Scholar 

  3. Liu, D., Tian, Y.: Application of extension data mining in student achievement analysis. CAAI Trans. Intell. Syst. 17(4), 707–713 (2022)

    Google Scholar 

  4. Liu, X.-Y., Liu, H.-Y., et al.: Research on student achievement prediction based on multiple linear regression. Comput. Technol. Dev. 32(3), 203–208 (2022)

    MathSciNet  Google Scholar 

  5. Hu, L.Q., Zhao, G.: Research on influencing factors of machine learning algorithm on student achievement based on data mining. J. Nanchang Hangkong Univ. Nat. Sci. 35(3), 43–48 (2021)

    Google Scholar 

  6. Zhou, S.: The application of data warehouse and data mining in grade analysis of students majoring in computer application in secondary vocational school. China West Normal University (2020)

    Google Scholar 

  7. Xu, Q., Li, J., Wang, Y.-M., Zhang, L.-L.: Student achievement analysis and visualization based on apriority algorithm. J. Tonghua Normal Univ. 44(4), 81–87 (2019)

    Google Scholar 

  8. Liu, A.: Application of Data Mining in the Analysis of Colleges Students’ Performance, Huaqiao University (2016)

    Google Scholar 

  9. Guo, Y.N.: Research on the application of data warehouse technology in the analysis of students’ performance. Harbin Normal University (2017)

    Google Scholar 

  10. Li, C.: Application analysis of data warehouse and data mining in student achievement analysis. China New Commun. 19(17), 136–138 (2017)

    Google Scholar 

  11. Jia, Y., Yang, G.: A study on Databank’s application in students’ score analysis. J. Shaanxi Youth Vocat. Coll. (1), 38–42 (2017)

    Google Scholar 

  12. Dai, Q., Li, Z.: Research on construction of learning behavior data warehouse. Softw. Guide 17(10), 187–190 (2018)

    Google Scholar 

  13. Zhang, X., Ma, Y., Yu, M.: The research on applying data warehouse to educational administration in institutions of higher learning. J. Anshan Normal Univ. 045(2), 83–85 (2003)

    Google Scholar 

  14. Wang, J.-M., Tang, N., Yang, D.: On the teaching quality according to the analysis of students’ scores. J. Chongqing Univ. Soc. Sci. Ed. 12(1) (2006)

    Google Scholar 

  15. Zhuang, Q.: Constructing conceptual model of data warehouse based on E-R schema. Comput. Eng. Appl. 10(1), 195–200 (2004)

    Google Scholar 

  16. Yang, Y., Deng, H., Lai, S.: Application of data warehouse in college student’s academic performance management. J. Southwest Univ. Nationalities⋅Nat. Sci. Ed. 35(3), 619–621 (2009)

    Google Scholar 

  17. Yang, X., Han, X.: Model designing and implementation of data warehouse based on the analysis of students’ score. Shanxi Electron. Technol. (1), 11–12+20 (2005)

    Google Scholar 

  18. Meng, Y., Huang, Z.: The application of data warehouse technique to educational management of university. J. Xuzhou Normal Univ. 21(2), 69–78 (2003)

    MathSciNet  Google Scholar 

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Acknowledgement

This work was supported by the Hainan Provincial Natural Science Foundation of China (project number: 622RC723) and the Education Department of Hainan Province (project number: Hnky2023-72).

Author information

Authors and Affiliations

  1. Information Technology School, Hainan College of Economics and Business, Haikou, 571127, Hainan, China

    Juntao Chen & Fei Tian

  2. School of Information Science and Technology, Qiongtai Normal University, Haikou, 571127, Hainan, China

    Jinmei Zhan

Authors
  1. Juntao Chen
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  2. Jinmei Zhan
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  3. Fei Tian
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Corresponding author

Correspondence to Jinmei Zhan .

Editor information

Editors and Affiliations

  1. Harbin Engineering University, Harbin, China

    Zhiwen Yu

  2. Harbin Engineering University, Harbin, China

    Qilong Han

  3. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Hongzhi Wang

  4. Northwestern Polytechnical University, Xi'an, China

    Bin Guo

  5. Shiga University, Shiga, Japan

    Xiaokang Zhou

  6. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  7. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Chen, J., Zhan, J., Tian, F. (2023). Research on the Construction of a Data Warehouse Model for College Student Performance. In: Yu, Z., et al. Data Science. ICPCSEE 2023. Communications in Computer and Information Science, vol 1880. Springer, Singapore. https://doi.org/10.1007/978-981-99-5971-6_29

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  • DOI: https://doi.org/10.1007/978-981-99-5971-6_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5970-9

  • Online ISBN: 978-981-99-5971-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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