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Epistemic Network Analysis Visualization

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Advances in Quantitative Ethnography (ICQE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1522))

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Abstract

Visualization plays an important role in Epistemic Network Analysis (ENA), not only in graphical representation but also to facilitate interpretation and communicate research findings. However, there is no published description of the design features behind ENA network graphs. This paper provides this description from a graphic design perspective, focusing on the design principles that make ENA network graphs aesthetically pleasing and intuitive to understand. By reviewing graphic design principles and examining other extant network visualizations, we show how the current ENA network graphs highlight the most important network characteristics and facilitate sense-making.

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References

  1. Allen, E.A., Erhardt, E.B.: Visualizing scientific data. In: Cacioppo, J.T., Tassinary, L.G., Berntson, G.G. (eds.) Cambridge Handbooks in Psychology. Handbook of Psychophysiology, pp. 679–697. Cambridge University Press, Cambridge (2017)

    Google Scholar 

  2. Battista, G.D., Eades, P., Tamassia, R., Tollis, I.G.: Graph Drawing: Algorithms for the Visualization of Graphs. Prentice Hall PTR, Hoboken (1998)

    MATH  Google Scholar 

  3. Bowman, D., et al.: The mathematical foundations of epistemic network analysis. In: Ruis, A.R., Lee, S.B. (eds.) ICQE 2021. CCIS, vol. 1312, pp. 91–105. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-67788-6_7

    Chapter  Google Scholar 

  4. Bradley, S.: Design Fundamentals: Elements, Attributes, and Principles. Vanseo Design, Colorado (2013)

    Google Scholar 

  5. Csardi, M.G.: Package ‘igraph.’ Netw. Anal. Vis. 3(09), 2013 (2013)

    Google Scholar 

  6. Eades, P.: A heuristic for graph drawing. Congr. Numer. 42, 149–160 (1984)

    MathSciNet  Google Scholar 

  7. Evergreen, S., Metzner, C.: Design principles for data visualization in evaluation. New Dir. Eval. 2013(140), 5–20 (2013)

    Article  Google Scholar 

  8. Fernandez-Nieto, G.M., Martinez-Maldonado, R., Kitto, K., Shum, S.B.: Modelling spatial behaviours in clinical team simulations using epistemic network analysis: methodology and teacher evaluation. In: LAK21: 11th International Learning Analytics and Knowledge Conference (2021).https://doi.org/10.1145/3448139.3448176

  9. Few, S., Edge, P.: Data Visualization: Past, Present, and Future. IBM Cognos Innovation Center (2007)

    Google Scholar 

  10. Fruchterman, T.M., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Exp. 21(11), 1129–1164 (1991)

    Article  Google Scholar 

  11. Gibson, H., Faith, J., Vickers, P.: A survey of two-dimensional graph layout techniques for information visualisation. Inf. Vis. 12(3–4), 324–357 (2013)

    Article  Google Scholar 

  12. Kaliisa, R., Misiejuk, K., Irgens, G.A., Misfeldt, M.: Scoping the emerging field of quantitative ethnography: opportunities, challenges and future directions. In: Ruis, A.R., Lee, S.B. (eds.) ICQE 2021. CCIS, vol. 1312, pp. 3–17. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-67788-6_1

    Chapter  Google Scholar 

  13. Kobourov, S.G.: Force-directed drawing algorithms. In: Handbook of Graph Drawing and Visualization (2013)

    Google Scholar 

  14. Kwon, O.H., Crnovrsanin, T., Ma, K.L.: What would a graph look like in this layout? a machine learning approach to large graph visualization. IEEE Trans. Visual Comput. Graph. 24(1), 478–488 (2017)

    Article  Google Scholar 

  15. Lok, S., Feiner, S., Ngai, G.: Evaluation of visual balance for automated layout. In: Proceedings of the 9th International Conference on Intelligent User Interfaces, pp. 101–108 (2004)

    Google Scholar 

  16. Samara, T.: Design Elements: A Graphic Style Manual. Rockport Press, Beverly (2007)

    Google Scholar 

  17. Shum, S.B.: Quantitative ethnography visualizations as tools for thinking keynote. In: International Conference on Quantitative Ethnography (2021)

    Google Scholar 

  18. Shaffer, D.W.: Quantitative Ethnography. Cathcart Press, Madison (2017)

    Google Scholar 

  19. Shaffer, D., Ruis, A.: Epistemic network analysis: a worked example of theory-based learning analytics. Handbook of Learning Analytics (2017)

    Google Scholar 

  20. Tamassia, R. (ed.): Handbook of Graph Drawing and Visualization. CRC Press, Boca Raton (2013)

    MATH  Google Scholar 

  21. Von Landesberger, T., et al.: Visual analysis of large graphs: State-of-the-Art and future research challenges. Comput. Graph. Forum 30(6), 1719–1749 (2011). Blackwell Publishing Ltd., Oxford

    Article  Google Scholar 

  22. Watzman, S.: Visual design principles for usable interfaces. In: The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications, pp. 263–285 (2003)

    Google Scholar 

  23. Ware, C.: Information Visualization: Perception for Design. Morgan Kaufmann Publishers, Burlington (2000)

    Google Scholar 

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Acknowledgements

This work was funded in part by the National Science Foundation (DRL-1661036, DRL-1713110), the Wisconsin Alumni Research Foundation, and the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison. The opinions, findings, and conclusions do not reflect the views of the funding agencies, cooperating institutions, or other individuals.

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Authors and Affiliations

  1. Wisconsin Center for Education Research, University of Wisconsin–Madison, Madison, WI, USA

    Yuanru Tan, Cesar Hinojosa, Cody Marquart, Andrew R. Ruis & David Williamson Shaffer

Authors
  1. Yuanru Tan
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  2. Cesar Hinojosa
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  3. Cody Marquart
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  4. Andrew R. Ruis
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  5. David Williamson Shaffer
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Corresponding author

Correspondence to Yuanru Tan .

Editor information

Editors and Affiliations

  1. University of Bergen, Bergen, Norway

    Barbara Wasson

  2. Semmelweis University, Budapest, Hungary

    Szilvia Zörgő

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Tan, Y., Hinojosa, C., Marquart, C., Ruis, A.R., Shaffer, D.W. (2022). Epistemic Network Analysis Visualization. In: Wasson, B., Zörgő, S. (eds) Advances in Quantitative Ethnography. ICQE 2021. Communications in Computer and Information Science, vol 1522. Springer, Cham. https://doi.org/10.1007/978-3-030-93859-8_9

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  • DOI: https://doi.org/10.1007/978-3-030-93859-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93858-1

  • Online ISBN: 978-3-030-93859-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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