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Genetic Algorithm of the Mutual Selection Between Teachers and Students in Online Learning

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Cyber Security Intelligence and Analytics (CSIA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1146))

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Abstract

With the development of education, computer application has penetrated into all aspects of people’s life. Computer makes the complicated data management work easy and efficient. In addition to the major, the current university courses are studied by students’ self selected subjects. This system can meet the choice wishes of teachers and students as much as possible, accelerate the speed of selection and matching, and change the shortcomings of the previous manual course arrangement. In this paper, when we study the system of teachers and students’ mutual selection, we focus on building a mathematical model of teachers and students’ mutual selection, combining with the theory of genetic algorithm, to explore a suitable algorithm to solve the problem of automatic combination and collocation in the process of teachers and students’ mutual selection. At the same time, we use MATLAB software to generate a system of teachers and students’ two-way selection based on genetic algorithm.

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References

  1. Wang, Z., Jiang, P.: A game between personality of new teachers in universities and personality of college students. J. High. Educ. 16, 351–357 (2017). (in Chinese)

    Google Scholar 

  2. Wella, W., Tjhin, V.U.: Exploring effective learning resources affecting student behavior on distance education. In: 10th Human System Interactions, vol. 7, pp. 253–256 (2017)

    Google Scholar 

  3. Bognar, B., Krumes, I.: Encouraging reflection and critical friendship in pre-service teacher education. Cent. Educ. Policy Stud. J. 1, 213–218 (2017)

    Google Scholar 

  4. Jansi Rani, M., Devaraj, D.: Two-stage hybrid gene selection using mutual information and genetic algorithm for cancer data classification. J. Med. Syst. 8, 191–197 (2019)

    Google Scholar 

  5. Pettersson, G., Ström, K.: Professional collaboration between class teachers and special educators in swedish rural schools. Br. J. Spec. Educ. 6, 123–128 (2019)

    Google Scholar 

  6. Liu, H., Ditzler, G.: Speeding up joint mutual information feature selection with an optimization heuristic. Comput. Intell. 2, 454–460 (2018)

    Google Scholar 

  7. Lan, W.: A factor-adjusted multiple testing procedure with application to mutual fund selection. J. Bus. Econ. Stat. 4, 203–210 (2019). (in Chinese)

    MathSciNet  Google Scholar 

  8. Zhang, H., Hong, H.: Feature selection in SVM based on the hybrid of enhanced genetic algorithm and mutual information. Lect. Notes Comput. Sci. 12, 557–562 (2017). (in Chinese)

    Google Scholar 

  9. Liu, G., Guli, N.M.: Analysis and investigation of emotional relationship between the teachers and the students and students’ evaluation of teaching in colleges. J. High. Educ. Res. 11, 263–268 (2015)

    Google Scholar 

  10. Huang, J., Rong, P.: A hybrid genetic algorithm for feature selection based on mutual information. Inf. Theory Stat. Learn. 12, 125–130 (2017). (in Chinese)

    MATH  Google Scholar 

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Acknowledgements

This work was supported by 2019 national innovation and entrepreneurship training project “Intelligent Learning Table” (Project No.: 201913207031) of Dalian University of Science and Technology.

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Correspondence to Jingjing Jiang .

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Jiang, J., Guan, S., Wang, J., Wang, D., Song, X. (2020). Genetic Algorithm of the Mutual Selection Between Teachers and Students in Online Learning. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_102

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