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Multi-dimensional Data Optimal Classification Algorithm for Quality Evaluation of Distance Teaching in Universities

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Abstract

In order to effectively extract the multi-dimensional data of teaching quality evaluation and accurately evaluate the quality of network distance teaching quality in universities, an optimal classification algorithm for network distance teaching quality evaluation is proposed. From the perspectives of teaching attitude, teaching skill, teaching skill, teaching content, teaching method and means, the quality evaluation indices of network distance teaching is designed. Combined with the evaluation indices, the multi-dimensional data mining method based on OLAP technology is used to mine the required multi-dimensional data of teaching quality evaluation in the distance teaching data warehouse of universities, the required multi-dimensional data is input into SVM algorithm to solve the optimal classification hyperplane of multi-dimensional data and implement the optimal classification of multi-dimensional data. The quality of distance teaching is evaluated by improving the salp group algorithm and setting the penalty factor and kernel function of SVM algorithm. The experimental results show that the classification accuracy of this method for multidimensional data is over 90%, and the evaluation accuracy is as high as 99%, it can extract multi-dimensional teaching quality evaluation from the network distance teaching data, which has good classification effect and can improve the accuracy of network distance teaching quality evaluation.

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References

  1. Liu S, Li Y, Fu W (2022) Human-centered attention-aware networks for action recognition. Int J Intell Syst 37(12):10968–10987

    Article  Google Scholar 

  2. Liu S, He T, Li J, Li Y, Kumar A (2023) An effective learning evaluation method based on text data with real-time attribution - a case study for mathematical class with students of junior middle school in China. ACM Trans Asian Low-Resource Lang Inf Process 22(3):63

    Google Scholar 

  3. Oktariyana AM, Sulaiman I (2021) Design of mobile learning rhythmic gymnastics materials for high school / vocational high school levels as a distance learning media during the covid-19 pandemic. Sports Eng 9(3):394–402

    Google Scholar 

  4. Zhang J (2021) Research on classroom teaching evaluation and instruction system based on GIS mobile terminal. Mob Inf Syst 2021(11):1–11

    Google Scholar 

  5. Yue Q, Wen X (2019) Application of improved GA-BP neural network in teaching quality evaluation. J Nat Sci Heilongjiang Univ 36(3):353–358

    Google Scholar 

  6. Xiao LP, Tian ZJ, Tian JW (2022) Research on teaching quality evaluation based on hidden Markov algorithm. Heilongjiang Res Higher Educ 40(1):151–155

    Google Scholar 

  7. Lei WP, Ma HM, Huang HM (2021) Evaluate teaching performance by residuals of student achievement. J East China Normal Univ (Educ Sci) 39(7):84–91

    Google Scholar 

  8. Queiroz-Sousa PO, Salgado AC (2020) A review on OLAP technologies applied to information networks. ACM Trans Knowl Discov Data 14(1):1–25

    Article  Google Scholar 

  9. Shi SH, Ding SF (2020) Energy-based structural least square twin support vector machine. CAAI Trans Intell Syst 15(05):1013–1019

    Google Scholar 

  10. Ahammad F (2021) A study of teaching effectiveness, scientific attitude and achievement in geography among higher secondary school students. Asian J Multidim Res (AJMR) 10(4):124–136

    Article  Google Scholar 

  11. Yusuf FN, Novita OE (2020) EFL teachers’ perceived language proficiency and teaching effectiveness. Indones J Appl Linguist 9(3):580–588

    Article  Google Scholar 

  12. Sun CY (2019) Design and implementation of teaching quality data platform based on analytic hierarchy process. Video Eng 43(04):94–98

    Google Scholar 

  13. Hell M, Knežević A, Babić Z (2021) Multicriteria analysis of the quality of teaching process in higher education: how to evaluate implementation of critical thinking. Cro Oper Res Rev 12:15–26

    Article  Google Scholar 

  14. Erraissi A (2019) Meta-modeling of big data visualization layer using on-line analytical processing (OLAP). Int J Adv Trends Comput Sci Eng 8(4):990–998

    Article  Google Scholar 

  15. Vaisman AA, Ahmed W, Zimanyi E (2020) A Temporal multidimensional model and OLAP operators. Int J Data Warehouse Min 16(6):1–32

    Google Scholar 

  16. Stankova EN, Balakshiy AV, Petrov DA, Korkhov VV, Shorov AV (2019) OLAP technology and machine learning as the tools for validation of the numerical models of convective clouds. Int J Bus Intell Data Min 14(1–2):254–266

    Google Scholar 

  17. Kopaev AY, Murakhovsky IA, Kuchmenko TA (2020) Intensification of data processing and obtaining new information on multidimensional signals of the "electronic nose". Proc Voronezh State Univ Eng Technol 82(1):247-251

  18. Zhang YS, Zhang YY, Wang S (2019) A novel in-memory OLAP star join acceleration technique with vector index. Chin J Comput 42(08):1686–1703

    Google Scholar 

  19. Liu Y, Ji JM, Li N, Zeng Y, Li JX, Zhu SQ, Kang J (2021) Research on the construction of MOOC teaching quality evaluation system from the perspectives of students: Taking academic information literacy MOOC courses as an example. Library J 40(2):95–103

    Google Scholar 

  20. Yao LH, Yu GZ (2019) Relational database information resource retrieval result classification method simulation. Comput Simul 36(1):445–448

    Google Scholar 

  21. Xiang CZ, Fu NX, Gadekallu TR (2022) Design of resource matching model of intelligent education system based on machine learning. EAI Endorsed Trans Scalable Inf Syst 9(6):e1

    Google Scholar 

  22. Guomin C, Pengrun C, Wenxia H, Jie Z (2022) Continuance intention mechanism of middle school student users on online learning platform based on qualitative comparative analysis method. Math Probl Eng 2022:3215337

    Google Scholar 

  23. Liu Y, Wang K, Liu L, Lan H, Lin L (2022) Tcgl: Temporal contrastive graph for self-supervised video representation learning. IEEE Trans Image Process 31:1978–1993. https://doi.org/10.1109/TIP.2022.3147032

    Article  Google Scholar 

  24. Zheng W, Zhou Y, Liu S, Tian J, Yang B, ... Yin L (2022) A deep fusion matching network semantic reasoning model. Appl Sci 12(7):3416.https://doi.org/10.3390/app12073416

  25. Cao H (2022) Entrepreneurship education-infiltrated computer-aided instruction system for college Music Majors using convolutional neural network. Front Psychol 13:900195. https://doi.org/10.3389/fpsyg.2022.900195

    Article  Google Scholar 

  26. Tang CF, Fakih A, Abosedra S (2022) The fatality rate of COVID-19: How does education, health infrastructure and institutional quality make a change? Margin: J Appl Econ Res 16(2):166–182

    Article  Google Scholar 

  27. McCord KH, Ayer SK, Perry LA, Patil KR, London JS, Khoury V, Wu W (2022) Student approaches and performance in element sequencing tasks using 2d and augmented reality formats. Educ Sci 12(4):247

    Article  Google Scholar 

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Authors and Affiliations

  1. College of Information Engineering, Xizang Minzu University, Xianyang, 712082, China

    Feng Chen

  2. Zhongda Group, Jiaxing, 314312, China

    Thippa Reddy Gadekallu

  3. Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon

    Thippa Reddy Gadekallu

  4. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, 632014, India

    Thippa Reddy Gadekallu

  5. College of Information Science and Engineering, Jiaxing University, Jiaxing, 314001, China

    Thippa Reddy Gadekallu

  6. Division of Research and development, Lovely Professional University, Phagwara, India

    Thippa Reddy Gadekallu

Authors
  1. Feng Chen
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  2. Thippa Reddy Gadekallu
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Contributions

Feng Chen contributed to Writing—Original Draft, Methodology, and Conceptualization; Thippa Reddy Gadekallu is contributed to Conceptualization and Writing—Review and Editing.

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Correspondence to Thippa Reddy Gadekallu.

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Chen, F., Gadekallu, T.R. Multi-dimensional Data Optimal Classification Algorithm for Quality Evaluation of Distance Teaching in Universities. Mobile Netw Appl 28, 889–899 (2023). https://doi.org/10.1007/s11036-023-02186-8

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  • DOI: https://doi.org/10.1007/s11036-023-02186-8

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