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Innovative design of an art teaching quality evaluation system based on big data and an association rule algorithm from the perspective of sustainable development

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Abstract

Online art courses suffer from poor course production, limited sustainable use and development, and a significant degree of course similarity. It is important to figure out how to create an efficient system for evaluating art instruction. In this article, we look at the current institutions of higher art education and how to use data mining techniques in the system for judging the quality of teaching. Using an association rule algorithm to solve the current teaching quality evaluation of rationality and subjectivity and a teaching quality evaluation algorithm based on association were some of the solutions used, and data mining effectively dredged out the indicators of the institutions of higher art education's teaching quality evaluation system. The widely used development tools, SQL Server and ASP.NET, were used to build and implement the teaching quality assessment system through a variety of indications of teaching quality evaluation in a school. The main contribution of this paper is the development of an effective teaching quality evaluation system index for higher art colleges, as well as the development of teacher–student interaction based on the comprehensive support of the Internet, in order to identify the factors influencing the teaching quality of design art colleges. The administrators of higher art education institutions will receive analytical materials for making decisions from this study that are based on science and objectivity. The results of the experimental process were quite effective.

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References

  • Alsuwaida N (2022) Online courses in art and design during the coronavirus (COVID-19) pandemic: teaching reflections from a first-time online instructor. SAGE Open 12(1):21582440221079828

    Article  Google Scholar 

  • Balla T, Radványi T, Király S, Király R (2018) Efficiency test of Microsoft SQL Server 2016. In: the 10th international conference on applied informatics

  • Cachia R, Ferrari A, Ala-Mutka K, Punie Y (2010) Creative learning and innovative teaching: final report on the study on creativity and innovation in education in EU member states (No. JRC62370). Institute for Prospective and Technological Studies, Joint Research Centre

  • Chang Z, Ma S, Mao B (2022) Machine learning-based correlation analysis of 5G cloud network alerts in big data scenarios. Post Telecom Des Technol 06:71–76

    Google Scholar 

  • El Boudani B, Kanaris L, Kokkinis A, et al (2020) Implementing deep learning techniques in 5G IoT networks for 3D indoor positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture). Sensors 20(19):5495

    Article  Google Scholar 

  • Gabriel A, Monticolo D, Camargo M et al (2016) Creativity support systems: a systematic mapping study. Think Skills Creat 21:109–122

    Article  Google Scholar 

  • Gao B (2022) Research and implementation of intelligent evaluation system of teaching quality in universities based on artificial intelligence neural network model. Math Probl Eng 2022:1–10

    Article  Google Scholar 

  • Guo X, Guo P, Feng L (2006) Implementation of teaching quality analysis and evaluation system based on data mining technology. J Northeast Dianli Univ 03:70–73

    Google Scholar 

  • Huang XH, Lee CK (2015) Disclosing Hong Kong teacher beliefs regarding creative teaching: five different perspectives. Think Skills Creat 15:37–47

    Article  Google Scholar 

  • Kan A, Zhang Y, Tax Y, Zhao Y, Wu B, He J, Zhu L (2022) Optimization of geography curriculum system for the construction of first-class disciplines--a study based on data mining of geography disciplines in 62 universities. World Geogr Res:1–14

  • Li Y, Qu C (2019) College english education platform based on browser/server structure and flipped classroom. Int J Emerg Technol Learn. https://doi.org/10.3991/ijet.v14i15.11147

    Article  Google Scholar 

  • Ma W, Yang Z (2020) Evaluation of teaching quality in higher vocational colleges based on quantum behaviour particle swarm optimization. J Phys Conf Ser 1629:012042

    Article  Google Scholar 

  • Mao Y, Zhu Y, Zhang S, Zhang D, Zhang F, Fan X (2019) Detecting interest-factor influenced abnormal evaluation of teaching via multimodal embedding and priori knowledge based neural network. In: 2019 IEEE Intl conf on parallel and distributed processing with applications, big data and cloud computing, sustainable computing and communications, social computing and networking (ISPA/BDCloud/SocialCom/SustainCom) (pp 1201–1209). IEEE

  • Metzger MJ (2007) Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research. J Am Soc Inform Sci Technol 58(13):2078–2091

    Article  Google Scholar 

  • Shan H (2022) Research on the application of data mining technology in teaching quality monitoring and evaluation system of universities. Off Autom 27(08):41–43

    Google Scholar 

  • Su S, Qu W, Wu Y, Yang Z (2021) Intelligent evaluation scheme of ideological and political education quality of college English course based on AHP under the background of big data. In: 2021 6th international conference on smart grid and electrical automation (ICSGEA) 2021 May 29 (pp 519–522). IEEE

  • Tsoi RHL (2001) Using analytic hierarchy process (AHP) method to prioritise human resources in substitution problem. Int J Comput Internet Manage 9(1):36–45

    Google Scholar 

  • Xu W (2022) Application of big data technology in comprehensive evaluation of teaching quality. Electron Technol 51(06):200–201

    Google Scholar 

  • Zhai S, Wang H, Sun Z, Wang S, Zhao H (2022) Application of association rules in the design of virtual maintenance course assessment. Mil Autom 41(06):47–52

    Google Scholar 

  • Zhang Z, Wu W, Wu D (2021) A Multi-Mode Learning Behavior Real-time Data Acquisition Method Based on Data Quality. In: 2021 2nd international symposium on computer engineering and intelligent communications (ISCEIC) 2021 Aug 6 (pp 64–69). IEEE

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Authors and Affiliations

  1. School of Film and Animation, Hubei Institute of Fine Arts, Wuhan, 430205, China

    Gang Zhou

  2. Faculty of Innovation and Design, City University of Macau, Macau, 999078, China

    Rui Zhan

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  1. Gang Zhou
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  2. Rui Zhan
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Correspondence to Rui Zhan.

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Zhou, G., Zhan, R. Innovative design of an art teaching quality evaluation system based on big data and an association rule algorithm from the perspective of sustainable development. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08028-9

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