CLOSED Call for Papers: Special Issue on Visualization Education and Teaching Visualization Literacy
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Submissions Due: 28 April 2021
Visualization literacy is the ability to read, write, and create graphical representation of data using digital or physical artefacts. 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 understand and use visualizations to prevent misuse and misinterpretation of visually represented data. Visualization literacy includes skills related to the design, reading, interpretation, critical discussion, interaction, and effective communication with data and visualizations. 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 visualization literacy skills for specific sectors (e.g., professionals in an industry, children, etc.) and general audiences. In addition, visualization 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. However, building knowledge around teaching, learning visualization, and visualization literacy is challenging because of the open and broad nature of visualization and its wide application to different domains and audiences that engage in a variety of activities following different conventions.
This special issue calls for groundbreaking work that advances knowledge about 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 and activities (e.g., schemas, tools, cheat sheets, toolkits) we use to educate (e.g., design cards, sketching, physicalizing, elicitation, peer feedback). Answers to these questions are crucial, to not only new university faculty and visualization instructors (few of whom 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, and data science.
Topics of interest include:
Learning materials, tools, and resources to support in-class learning and beyond
Learning goals, skill sets, and 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, materials, classes, and methods
Assessment strategies to test for visualization knowledge and literacy
Teaching activities for in-class engagement (classroom, workshops, etc.)
Teaching approaches and methodology
Surveys and reviews on teaching methods and materials for visualization
Ethical, social, and critical considerations on visualization education