IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v468y2017icp740-749.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116309499
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2016.11.126?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Sixin & Mei, Jun & Xia, Dan & Yang, Zhanying & Hu, Junhao, 2022. "Finite-time optimal feedback control mechanism for knowledge transmission in complex networks via model predictive control," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xie, Yingkang & Wang, Zhen, 2021. "Transmission dynamics, global stability and control strategies of a modified SIS epidemic model on complex networks with an infective medium," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 23-34.
    2. Lu, Peng & Yao, Qi & Lu, Pengfei, 2019. "Two-stage predictions of evolutionary dynamics during the rumor dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 349-369.
    3. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.
    4. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
    5. Lu, Peng & Deng, Liping & Liao, Hongbing, 2019. "Conditional effects of individual judgment heterogeneity in information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 335-344.
    6. 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).
    7. Wang, Haiying & Wang, Jun & Ding, Liting & Wei, Wei, 2017. "Knowledge transmission model with consideration of self-learning mechanism in complex networks," Applied Mathematics and Computation, Elsevier, vol. 304(C), pages 83-92.
    8. Jiancheng Guan & Wenjia Zhu, 2014. "How knowledge diffuses across countries: a case study in the field of management," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2129-2144, March.
    9. Jia, Pingqi & Wang, Chao & Zhang, Gaoyu & Ma, Jianfeng, 2019. "A rumor spreading model based on two propagation channels in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 342-353.
    10. 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).
    11. Wei, Xiaodan & Zhao, Xu & Zhou, Wenshu, 2022. "Global stability of a network-based SIS epidemic model with a saturated treatment function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    12. Huo, Liang’an & Jiang, Jiehui & Gong, Sixing & He, Bing, 2016. "Dynamical behavior of a rumor transmission model with Holling-type II functional response in emergency event," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 228-240.
    13. Widad Guechtouli, 2014. "Agent-based modeling of knowledge transfer within social networks," Working Papers 2014-148, Department of Research, Ipag Business School.
    14. Wang, Tao & He, Juanjuan & Wang, Xiaoxia, 2018. "An information spreading model based on online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 488-496.
    15. 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.
    16. 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.
    17. Sahafizadeh, Ebrahim & Tork Ladani, Behrouz, 2018. "The impact of group propagation on rumor spreading in mobile social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 412-423.
    18. Zhang, Yuhuai & Zhu, Jianjun, 2018. "Stability analysis of I2S2R rumor spreading model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 862-881.
    19. Wang, Jinling & Jiang, Haijun & Hu, Cheng & Yu, Zhiyong & Li, Jiarong, 2021. "Stability and Hopf bifurcation analysis of multi-lingual rumor spreading model with nonlinear inhibition mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    20. Rui, Xiaobin & Meng, Fanrong & Wang, Zhixiao & Yuan, Guan & Du, Changjiang, 2018. "SPIR: The potential spreaders involved SIR model for information diffusion in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 254-269.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:740-749. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.