Abstract
Visualization can be a powerful tool to enhance learning and to better support the learning process. Tailoring visualization to the specific audiences and goals of these situations can increase the likelihood of effective communication. In many cases, visualizations which require limited prior specific domain knowledge are helpful. Similarly, when crafting visualization development experiences for students in visualization courses, selecting easy-to-understand application domains for projects helps students to leverage their existing intuition about the domain in order to be able to focus on developing skills in visualization. Visualizations offer the potential to enrich educational settings, making concepts more engaging, concrete, and accessible. Visualizations for student audiences present both challenges and opportunities. The challenges are grounded in the potentially limited background knowledge of students, the need for examples to be engaging and accessible, and the need to support explicit curricular goals. The opportunities stem from a freedom to choose methods, data, and even application domains to address curriculum focus and learning objectives. This chapter discusses issues in adapting visualizations for educational settings, tuning visualizations to support curriculum goals, scaling visualization to fit on student devices, and crafting visualization development projects in course settings. The observations discussed in this chapter result from our experiences that include adapting visualizations produced by a science agency for the general public for use in the K-12 classroom, scaling and adapting interactive visualizations developed for a museum setting for classroom use, and designing visualization exercises and projects in a college-level computer science course.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Team members that equally contributed to the initial concept of the project: Helen-Nicole Kostis, Horace Mitchell, Neema Mostafavi, Wade Sisler, Christopher Smith, Michael Starobin. With database expertise provided by Joycelyn Thomson Jones.
- 2.
NASA Visualization Explorer Team: https://svs.gsfc.nasa.gov/nasaviz/credits.html.
- 3.
References
NASA Visualization Explorer. https://nasaviz.gsfc.nasa.gov/. Accessed 2019
Maryvale Preparatory School. https://www.maryvale.com/
Albert Einstein Distinguished Educator Fellowship (AEF) Program. https://science.energy.gov/wdts/einstein/
Degrees of reading power. http://www.questarai.com/assessments/district-literacy-assessments/degrees-of-reading-power/. Accessed 2019
Next science generation standards. https://www.nextgenscience.org/. Accessed 2019
Earth system science education alliance courses, NASA Viz app. http://essea.strategies.org/vizapp.php. Accessed 2019
Common core state standards initiative. http://www.corestandards.org/. Accessed 2019
Altieri, J.L.: Reading science: Practical strategies for integrating instruction. The Electronic Journal for English as a Second Language 20(4), (2017)
Bohlin, G., Göransson, A.C., Gericke, N., Tibell, L.A.E.: NTA-Digital – Tema Kroppen. In: FND 2016, Forskning i naturvetenskapernas didaktik (2016)
Chandler, P.: Dynamic visualisations and hypermedia: beyond the wow factor. Comput. Hum. Behav. 25(2), 389–392 (2009)
Cope, B., Kalantzis, M.: Multiliteracies: Literacy Learning and the Design of Social Futures. Psychology Press (2000)
Michaelsen, L.K., Knight, A.B., Fink, L.D.: Team-Based Learning: A Transformative use of Small Groups. Greenwood publishing group (2002)
Montaez, A.: How science visualization can help save the world (2016). https://blogs.scientificamerican.com/sa-visual/how-science-visualization-can-help-save-the-world/
Oemig, P.A.: Promoting science literate identities through the use of trade books. In: R.D. Tim Spuck T. Rust (ed.) Best practices in STEM education: innovative approaches from Einstein Fellow alumni, pp. 399–419. Peter Lang, New York (2018)
Rau, M.A.: Conditions for the effectiveness of multiple visual representations in enhancing stem learning. Educ. Psychol. Rev. 29(4), 717–761 (2017)
Rheingans, P.: Minor adventures in flipped classrooms, team-based learning, and other pedagogical buzzwords. In: Pedagogy of Data Visualization Workshop (2016)
Royal Swedish Academy of Engineering Sciences: NTA digital (2019). https://www.iva.se/projekt/nta-digital/
Schönborn, K.J., Anderson, T.R.: The importance of visual literacy in the education of biochemists. Biochem. Mol. Biol. Educ. 34(2), 94–102 (2006)
Schönborn, K.J., Anderson, T.R.: Bridging the educational research-teaching practice gap. Biochem. Mol. Biol. Educ. 38(5), 347–354 (2010)
Schönborn, K.J., Anderson, T.R.: Bridging the educational research-teaching practice gap: foundations for assessing and developing biochemistry students’ visual literacy. Biochem. Mol. Biol. Educ. 38(5), 347–354 (2010)
Schroeder, D., Keefe, D., Kowalewski, T., White, L., Carlis, J., Santos, E., Sweet, R., Lendvay, T., Reihsen, T.: Visualizing surgical training databases: exploratory visualization, data modeling, and formative feedback for improving skill acquisition. Computer Graphics and Applications (2012)
Scribner, S., Cole, M., Cole, M.: The Psychology of Literacy, vol. 198. Harvard University Press, Cambridge, MA (1981)
Shanahan, T., Shanahan, C.: Teaching disciplinary literacy to adolescents: rethinking content-area literacy. Harv. Educ. Rev. 78(1), 40–59 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Rheingans, P., Kostis, HN., Oemig, P.A., Robbins, G.B., Ynnerman, A. (2020). Reaching Broad Audiences in an Educational Setting. In: Chen, M., Hauser, H., Rheingans, P., Scheuermann, G. (eds) Foundations of Data Visualization. Springer, Cham. https://doi.org/10.1007/978-3-030-34444-3_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-34444-3_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34443-6
Online ISBN: 978-3-030-34444-3
eBook Packages: Computer ScienceComputer Science (R0)