IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v495y2018icp405-417.html
   My bibliography  Save this article

Modelling students’ knowledge organisation: Genealogical conceptual networks

Author

Listed:
  • Koponen, Ismo T.
  • Nousiainen, Maija

Abstract

Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students’ concept networks.

Suggested Citation

  • Koponen, Ismo T. & Nousiainen, Maija, 2018. "Modelling students’ knowledge organisation: Genealogical conceptual networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 405-417.
    • Handle: RePEc:eee:phsmap:v:495:y:2018:i:c:p:405-417
    DOI: 10.1016/j.physa.2017.12.105
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117313547
    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.2017.12.105?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. Lipowski, Adam & Lipowska, Dorota, 2012. "Roulette-wheel selection via stochastic acceptance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2193-2196.
    2. Chen, Chaomei & Chen, Yue & Horowitz, Mark & Hou, Haiyan & Liu, Zeyuan & Pellegrino, Donald, 2009. "Towards an explanatory and computational theory of scientific discovery," Journal of Informetrics, Elsevier, vol. 3(3), pages 191-209.
    3. Estrada, Ernesto & Higham, Desmond J. & Hatano, Naomichi, 2009. "Communicability betweenness in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 764-774.
    Full references (including those not matched with items on IDEAS)

    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. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    2. Stephen Carley & Alan L. Porter, 2012. "A forward diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 407-427, February.
    3. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    4. Souzanchi Kashani, Ebrahim & Roshani, Saeed, 2019. "Evolution of innovation system literature: Intellectual bases and emerging trends," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 68-80.
    5. Tian Wang & Zhaoping Yang & Xiaodong Chen & Fang Han, 2022. "Bibliometric Analysis and Literature Review of Tourism Destination Resilience Research," IJERPH, MDPI, vol. 19(9), pages 1-16, May.
    6. Xian Li & Ronald Rousseau & Liming Liang & Fangjie Xi & Yushuang Lü & Yifan Yuan & Xiaojun Hu, 2022. "Is low interdisciplinarity of references an unexpected characteristic of Nobel Prize winning research?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2105-2122, April.
    7. Florian Blöchl & Fabian J. Theis & Fernando Vega-Redondo & Eric O'N. Fisher, 2010. "Which Sectors of a Modern Economy are most Central?," CESifo Working Paper Series 3175, CESifo.
    8. Carlos Olmeda-Gómez & Maria-Antonia Ovalle-Perandones & Antonio Perianes-Rodríguez, 2017. "Co-word analysis and thematic landscapes in Spanish information science literature, 1985–2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 195-217, October.
    9. Huamei Shao & Gunwoo Kim & Qing Li & Galen Newman, 2021. "Web of Science-Based Green Infrastructure: A Bibliometric Analysis in CiteSpace," Land, MDPI, vol. 10(7), pages 1-19, July.
    10. Chen, Enming & Zhou, Zhongbao & Li, Ruiyang & Chang, Zhongxiang & Shi, Jianmai, 2024. "The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    11. Hamid Darvish & Yaşar Tonta, 2016. "Diffusion of nanotechnology knowledge in Turkey and its network structure," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 569-592, May.
    12. Huang, Cui & Yang, Chao & Su, Jun, 2021. "Identifying core policy instruments based on structural holes: A case study of China’s nuclear energy policy," Journal of Informetrics, Elsevier, vol. 15(2).
    13. Andrés Alfonso Rosales-Muñoz & Luis Fernando Grisales-Noreña & Jhon Montano & Oscar Danilo Montoya & Alberto-Jesus Perea-Moreno, 2021. "Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    14. Alsayed, Ahmad & Higham, Desmond J., 2015. "Betweenness in time dependent networks," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 35-48.
    15. Yang, Zhirou & Liu, Jing, 2018. "A memetic algorithm for determining the nodal attacks with minimum cost on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1041-1053.
    16. Wang, Shuai & Liu, Jing, 2016. "Robustness of single and interdependent scale-free interaction networks with various parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 139-151.
    17. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    18. Jake R. Nelson & Tony H. Grubesic, 2018. "Environmental Justice: A Panoptic Overview Using Scientometrics," Sustainability, MDPI, vol. 10(4), pages 1-18, March.
    19. Tungom, Chia E. & Wang, Hong & Beata, Kamuya & Niu, Ben, 2024. "SWOAM: Swarm optimized agents for energy management in grid-interactive connected buildings," Energy, Elsevier, vol. 301(C).
    20. Srayan Datta & Eytan Adar, 2018. "A generative model for scientific concept hierarchies," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-19, February.

    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:495:y:2018:i:c:p:405-417. 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.