[Infovis] CfP CG&A Special Issue on Visualization Education and Teaching Visualization Literacy: >April, 28, 2021.

[Benjamin Bach]

Dear Colleagues, 

It is our great pleasure to announce the call for papers for our Computer Graphics and Applications (CG&A) Special Issue on Visualization Education and Teaching Visualization Literacy. Please help us spread the word as we solicit submissions from across the disciplines. 

The deadline for submission is April 28, 2021 with a publication date around November/December 2021 (set by CG&A).

https://www.computer.org/digital-library/magazines/cg/call-for-papers-special-issue-on-visualization-education-and-teaching-visualization-literacy <https://www.computer.org/digital-library/magazines/cg/call-for-papers-special-issue-on-visualization-education-and-teaching-visualization-literacy>
Focus and relevance: 
	
Visualisation literacy is the ability to read, write and create visualizations of data using digital or physical representations. This is a key asset for any informed use and critical engagement with visual representations of data. With the increasing use of visualizations, it is becoming essential for everybody to be able to understand and use visualizations to prevent misuse and misinterpretation of visually represented data. Visualisation literacy includes skills related to the design, reading, interpretation, critical discussion, as well as interaction and effective communication with data and visualisations. While structured guidelines and extensive empirical knowledge exist on how to visually represent data, there is little foundational and empirical knowledge about how to teach and train visualisation literacy skills for specific sectors (e.g., professionals in an industry, children, etc.) and general audiences. In addition, visualisation literacy is key for a society of critical and informed citizens, effective analysts, informed decision-makers, and honest advocates for the use of data that supports human values. 

Building knowledge around teaching and learning visualization and visualization literacy is challenging because of the open and broad nature of visualisation and its wide application to different domains and  audiences that engage in a variety of activities following different conventions. 

This special issue calls for ground-breaking work to advance our knowledge around education in visualization. This includes advances in how to teach visualization to diverse audiences and in diverse settings; which skills to teach (e.g., design, critical thinking, data literacy, programming, interacting with data), in which contexts we teach visualization (e.g., storytelling, formal education, professional development, collaborations), to which audiences (e.g., scientists, developers, designers, collaborators) in which domains we teach visualization (e.g., data science, journalism, business), what forms visualization education can take (e.g., autodidactic learning, online learning, educating professionals, games, storytelling), and which materials (e.g., schemas, tools, cheat sheets, toolkits) and activities we use to educate (e.g., design cards, sketching, physicalizing, elicitation, peer feedback). 
 
Answers to these questions are crucial, not only to new university faculty and visualization instructors (few of which had the chance to enjoy formal training in pedagogy), but also practitioners in visualization, news agencies, museums, curriculum writers, businesses, school teachers, and many others. At the same time, being part of the global scientific community at the forefront of knowledge generation, it is our mission to engage with the wider community to transfer our knowledge in creative and effective ways. 

This Special Issue asks for original, unpublished, contributions—research, opinions, and surveys—from a wide variety of domains including visualization, pedagogy, social science, psychology, human-computer interaction, data science, and other related disciplines. 

Topics:
Learning material, tools, and resources to support in-class learning and beyond
Learning goals, skill sets, taxonomies
Visualization guidelines and approaches to making data visualization knowledge and practical skills available to a wider audience in a structured form
Guidelines to help novice teachers teach visualizations
Critical reflections on conducting visualization activities and classes (teaching experience),
Evaluation strategies for learning activities, material, classes, methods
Assessment strategies to test for visualization knowledge and literacy 
Teaching activities for in-class engagement (classroom, workshop, etc.)
Teaching approaches and methodology
Surveys and reviews on teaching methods and materials for visualization
Ethical, social, and critical considerations on visualization education
Studies on visualization literacy and engagement
Guest Editors:
Benjamin Bach, University of Edinburgh, bbach at ed.ac.uk <mailto:bbach at ed.ac.uk>
Samuel Huron, Institut Polytechnique de Paris samuel.huron at telecom-paris.fr <mailto:samuel.huron at telecom-paristech.fr>
Uta Hinrichs, University of St. Andrews, uh3 at st-andrews.ac.uk <mailto:uh3 at st-andrews.ac.uk>
Jonathan Roberts, Bangor University, j.c.roberts at bangor.ac.uk <mailto:j.c.roberts at bangor.ac.uk>
Sheelagh Carpendale, Simon Fraser University, sheelagh at sfu.ca <mailto:sheelagh at sfu.ca> 


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