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SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks

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  • Li, Jingjing
  • Zhang, Yumei
  • Man, Jiayu
  • Zhou, Yun
  • Wu, Xiaojun

Abstract

Cooperative learning is one of the most effective teaching methods, which has been widely used. Students’ mutual contact forms a cooperative learning network in this process. Our previous research demonstrated that the cooperative learning network has complex characteristics. This study aims to investigating the dynamic spreading process of the knowledge in the cooperative learning network and the inspiration of leaders in this process. To this end, complex network transmission dynamics theory is utilized to construct the knowledge dissemination model of a cooperative learning network. Based on the existing epidemic models, we propose a new susceptible–infected–susceptible-leader (SISL) model that considers both students’ forgetting and leaders’ inspiration, and a susceptible–infected–removed-leader (SIRL) model that considers students’ interest in spreading and leaders’ inspiration. The spreading threshold λcand its impact factors are analyzed. Then, numerical simulation and analysis are delivered to reveal the dynamic transmission mechanism of knowledge and leaders’ role. This work is of great significance to cooperative learning theory and teaching practice. It also enriches the theory of complex network transmission dynamics.

Suggested Citation

  • Li, Jingjing & Zhang, Yumei & Man, Jiayu & Zhou, Yun & Wu, Xiaojun, 2017. "SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 740-749.
    • Handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:740-749
    DOI: 10.1016/j.physa.2016.11.126
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    1. R. Cowan & N. Jonard & J. -B. Zimmermann, 2007. "Evolving networks of inventors," Springer Books, in: Uwe Cantner & Franco Malerba (ed.), Innovation, Industrial Dynamics and Structural Transformation, pages 129-148, Springer.
    2. Yang, Meng & Chen, Guanrong & Fu, Xinchu, 2011. "A modified SIS model with an infective medium on complex networks and its global stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2408-2413.
    3. Zhang, Jiancheng & Sun, Jitao, 2014. "Stability analysis of an SIS epidemic model with feedback mechanism on networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 24-32.
    4. Kiss, Istvan Z. & Broom, Mark & Craze, Paul G. & Rafols, Ismael, 2010. "Can epidemic models describe the diffusion of topics across disciplines?," Journal of Informetrics, Elsevier, vol. 4(1), pages 74-82.
    5. Bettencourt, Luís M.A. & Cintrón-Arias, Ariel & Kaiser, David I. & Castillo-Chávez, Carlos, 2006. "The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 513-536.
    6. Shi, Hongjing & Duan, Zhisheng & Chen, Guanrong, 2008. "An SIS model with infective medium on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2133-2144.
    7. Piergiuseppe Morone & Richard Taylor, 2004. "Knowledge diffusion dynamics and network properties of face-to-face interactions," Journal of Evolutionary Economics, Springer, vol. 14(3), pages 327-351, July.
    8. Xia, Ling-Ling & Jiang, Guo-Ping & Song, Bo & Song, Yu-Rong, 2015. "Rumor spreading model considering hesitating mechanism in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 295-303.
    9. Juang, Jonq & Liang, Yu-Hao, 2015. "Analysis of a general SIS model with infective vectors on the complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 382-395.
    10. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    11. Wen-Bao Lin, 2013. "Research on knowledge sharing and interpersonal relationships: empirical study of family firms and non-family firms," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 151-166, January.
    12. Qian, Zhen & Tang, Shaoting & Zhang, Xiao & Zheng, Zhiming, 2015. "The independent spreaders involved SIR Rumor model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 95-102.
    13. Li, Weihua & Tang, Shaoting & Pei, Sen & Yan, Shu & Jiang, Shijin & Teng, Xian & Zheng, Zhiming, 2014. "The rumor diffusion process with emerging independent spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 121-128.
    14. Bing Wu & Shan Jiang & Hsinchun Chen, 2015. "The impact of individual attributes on knowledge diffusion in web forums," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2221-2236, November.
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    Cited by:

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    2. Wang, Haiying & Wang, Jun & Small, Michael & Moore, Jack Murdoch, 2019. "Review mechanism promotes knowledge transmission in complex networks," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 113-125.
    3. Zhu, Hongmiao & Jin, Zhen & Yan, Xin, 2023. "A dynamics model of coupling transmission for multiple different knowledge in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    4. Wang, Haiying & Wang, Jun & Small, Michael, 2018. "Knowledge transmission model with differing initial transmission and retransmission process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 478-488.
    5. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    6. Liao, Shi-Gen & Yi, Shu-Ping, 2021. "Modeling and analyzing knowledge transmission process considering free-riding behavior of knowledge acquisition: A waterborne disease approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    7. Liao, Shi-Gen & Yi, Shu-Ping, 2021. "Modeling and analysis knowledge transmission process in complex networks by considering internalization mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    8. Zhu, He & Ma, Jing, 2018. "Knowledge diffusion in complex networks by considering time-varying information channels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 225-235.
    9. Nan Xu & Yaoqun Xu, 2022. "Research on Tacit Knowledge Dissemination of Automobile Consumers’ Low-Carbon Purchase Intention," Sustainability, MDPI, vol. 14(16), pages 1-26, August.
    10. Zenghui Yue & Haiyun Xu & Guoting Yuan & Yan Qi, 2022. "Modeling knowledge diffusion in the disciplinary citation network based on differential dynamics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7593-7613, December.
    11. Xiaodan Kong & Qi Xu & Tao Zhu, 2019. "Dynamic Evolution of Knowledge Sharing Behavior among Enterprises in the Cluster Innovation Network Based on Evolutionary Game Theory," Sustainability, MDPI, vol. 12(1), pages 1-23, December.

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