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IoT and Big Data Technologies for Health Care

IoTCare 2021: IoT and Big Data Technologies for Health Care pp 88–104Cite as

Effect Evaluation of College English Blended Teaching Based on Factor Analysis and Association Rules

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Abstract

In order to effectively evaluate the effect of College English blended teaching and optimize the implementation effect of College English teaching. Based on factor analysis and association rules, this paper proposes a study on the effect evaluation of College English blended teaching. Starting from the practice of practical English blended teaching mode, according to the characteristics of practical English blended teaching mode, based on factor analysis and association rules, this paper evaluates the effect of College English blended teaching by combining practice with theory. Through investigation and analysis, it is proved that blended teaching mode can optimize college English classroom teaching and improve students’ English practical ability. Further optimize the implementation effect of College English teaching.

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References

  1. Dou, Q.: Multimodal discourse analysis in the blended teaching of college English flipped class. Int. J. Electr. Eng. Educ. 11(5), 002072092110042 (2021)

    Article  Google Scholar 

  2. Yang, C., Huan, S., Yang, Y.: Application of big data technology in blended teaching of college students: a case study on rain classroom. Int. J. Emerg. Technol. Learn. (iJET) 15(11), 4 (2020)

    Article  Google Scholar 

  3. Wang, R.: Massive open online course platform blended english teaching method based on model-view-controller framework. Int. J. Emerg. Technol. Learn. (iJET) 14(16), 188 (2019)

    Article  Google Scholar 

  4. Bai, X., Gu, X.: Group differences of teaching presence, social presence, and cognitive presence in a xMOOC-based blended course. Int. J. Distance Educ. Technol. 19(2), 1–14 (2021)

    Article  Google Scholar 

  5. Malinee, V.V., Senthamarai, T.: The use of Web 2.0 tools in English for specific purpose: a blended learning approach in English language teaching. J. Shanghai Jiaotong Univ. (Sci.) 16(8), 703–716 (2020)

    Google Scholar 

  6. Guo, J., Bai, L., Yu, Z., et al.: An AI-application-oriented in-class teaching evaluation model by using statistical modeling and ensemble learning. Sensors 21(1), 241 (2021)

    Article  Google Scholar 

  7. Hu, J.: Teaching evaluation system by use of machine learning and artificial intelligence methods. Int. J. Emerg. Technol. Learn. (iJET) 16(5), 87 (2021)

    Article  Google Scholar 

  8. Zhang, X., Shi, W.: Research about the university teaching performance evaluation under the data envelopment method. Cogn. Syst. Res. 56, 108–115 (2019)

    Google Scholar 

  9. Zhu, Y., Lu, H., Qiu, P., et al.: Heterogeneous teaching evaluation network based offline course recommendation with graph learning and tensor factorization. Neurocomputing 415, 84–95 (2020)

    Article  Google Scholar 

  10. He, Y., Li, T.: A lightweight CNN model and its application in intelligent practical teaching evaluation. MATEC Web Conf. 309(4), 05016 (2020)

    Article  Google Scholar 

  11. Liu, S., Liu, G., Zhou, H.: A robust parallel object tracking method for illumination variations. Mob. Netw. Appl. 24(1), 5–17 (2018). https://doi.org/10.1007/s11036-018-1134-8

    Article  MathSciNet  Google Scholar 

  12. Liu, S., Bai, W., Liu, G., et al.: Parallel fractal compression method for big video data. Complexity 2018, 2016976 (2018)

    MATH  Google Scholar 

  13. Liu, S., He, T., Dai, J.: A survey of CRF algorithm based knowledge extraction of elementary mathematics in Chinese. Mobile Networks and Applications 26(5), 1891–1903 (2021). https://doi.org/10.1007/s11036-020-01725-x

    Article  Google Scholar 

  14. Jinyu, W.: Summative assessment of college English teachers’ teaching effect. IPPTA Q. J. Indian Pulp Pap. Tech. Assoc. 30(7), 876–882 (2018)

    Google Scholar 

  15. Chai, C., Damnoen, P.S., Phumphongkhochasorn, P.: Theory of planned behavior in support for post Covid-19 new normalization responses of teacherstowards online and blended learning. Solid State Technol. 63(5), 2166–2178 (2020)

    Google Scholar 

  16. Graham, C.R., Borup, J., Pulham, E., et al.: K–12 blended teaching readiness: model and instrument development. J. Res. Technol. Educ. 51, 239–258 (2019)

    Google Scholar 

  17. Xu, D., Glick, D., Rodriguez, F., et al.: Does blended instruction enhance English language learning in developing countries? Evidence from Mexico. Br. J. Educ. Technol. 51(1), 211–227 (2020)

    Google Scholar 

  18. Liontas, J.I., TESOL International Association, Dellicarpini, M.: The TESOL Encyclopedia of English Language Teaching || Introduction to Assessment and Evaluation, pp. 1–3 (2018)

    Google Scholar 

  19. Peng, R., Fu, R.: The effect of Chinese EFL students’ learning motivation on learning outcomes within a blended learning environment. Australas. J. Educ. Technol. 37, 61–74 (2021)

    Article  Google Scholar 

  20. Legesse, T., Anbessa, B., Temene, D., et al.: Evaluation of blended fertilizer formulas under limed condition of acid soil on soybean (Glycine max) at Asossa District of Benishal-gul Gumuz regional state. Int. J. Plant Soil Sci., 18–29 (2020)

    Google Scholar 

  21. Zinovieva, I.S., Artemchuk, V.O., Iatsyshyn, A.V., et al.: The use of MOOCs as additional tools for teaching NoSQL in blended and distance learning mode. J. Phys. Conf. Ser. 1946(1), 012011 (2021). 14pp

    Google Scholar 

  22. Thurab-Nkhosi, D., Maharaj, C., Ramadhar, V.: The impact of emergency remote teaching on a blended engineering course: perspectives and implications for the future. SN Soc. Sci. 1(7), 1–19 (2021)

    Article  Google Scholar 

  23. Zi, W., Zhou, Y.: Research-based College English blended teaching of fashion major: a case study of Beijing Institute of Fashion Technology. Int. J. Contemp. Educ. 3(2), 55 (2020)

    Article  Google Scholar 

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Funding

Funding.

In 2018, the key project of humanities and social sciences research in Anhui colleges and universities “Research on the construction of debate style based on dialogue syntax theory” phased results (project number: SK2018A0277); The 2018 Fuyang Normal University Humanities and Social Science Research General Project “The Cognitive Pragmatic Study of English Debate” (project number: 2018FSSK06).

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Authors and Affiliations

  1. Fuyang Normal University, Fuyang, 236037, China

    Rong-rong Ruan

  2. CSG Peak Shaving and Frequency Modulation Power Generation Co., Ltd., Guangzhou, 511400, China

    Meng Ye

Authors
  1. Rong-rong Ruan
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  2. Meng Ye
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Corresponding author

Correspondence to Meng Ye .

Editor information

Editors and Affiliations

  1. University of Leicester, Leicester, UK

    Shuihua Wang

  2. Harbin Institute of Technology, Shenzhen, China

    Zheng Zhang

  3. University of Jinan, Jinan, China

    Yuan Xu

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Ruan, Rr., Ye, M. (2022). Effect Evaluation of College English Blended Teaching Based on Factor Analysis and Association Rules. In: Wang, S., Zhang, Z., Xu, Y. (eds) IoT and Big Data Technologies for Health Care. IoTCare 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 414. Springer, Cham. https://doi.org/10.1007/978-3-030-94185-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-94185-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-94184-0

  • Online ISBN: 978-3-030-94185-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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