https://www.dagstuhl.de/22261
26. Juni – 01. Juli 2022, Dagstuhl-Seminar 22261
Visualization Empowerment: How to Teach and Learn Data Visualization
Organisatoren
Benjamin Bach (University of Edinburgh, GB)
Sheelagh Carpendale (Simon Fraser University – Burnaby, CA)
Uta Hinrichs (University of Edinburgh, GB)
Samuel Huron (Institut Polytechnique de Paris, FR)
Auskunft zu diesem Dagstuhl-Seminar erteilen
Christina Schwarz zu administrativen Fragen
Andreas Dolzmann zu wissenschaftlichen Fragen
Dokumente
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Motivation
The concept of visualization literacy encompasses the ability to read, write, and create visualizations of data using digital or physical representations and is becoming an important asset for a data-literate, informed, and critical society. While many useful textbooks, blogs, and courses exist about data visualization—created by both academics and practitioners—little is known about 1) how learning processes in the context of visualization unfold and 2) what the best practices are to engage and to teach the theory and practice of data visualization to diverse audiences, ranging from children to adults, from novices to the advanced, from students to professionals, and including different domain backgrounds.
The aim of this Dagstuhl Seminar is to collect, discuss, and systematize knowledge around the education and teaching of data visualization to empower people making effective and unbiased use of this powerful medium. To that end, we aim to:
- Provide a cohesive overview of the state-of-the-art in visualization literacy (materials, skills, evaluation, etc.) and compile a comprehensive handbook for academics, teachers, and practitioners;
- Collect and systematize learning activities to inform teaching visualization across a wide range of education scenarios in the form of a teaching activities cook-book.
- Discuss open challenges and outline future research agendas to improve visualization literacy and education. We aim to facilitate interdisciplinary research collaborations among attendees; researchers, practitioners, and educators from a wide range of backgrounds including data visualization, education, and data science.
The research questions we would like to discuss relate to four themes:
- Content of teaching and education, including learning goals, concepts, skills, practical and theoretical knowledge. Which resources, materials, and best practices exist today to teach visualization?
- Context and factors that define and inform the content and process of teaching and learning: audiences, their background and learning objectives, scenarios such as university, school, self-taught, and online learning, workshops in industry, at science fairs or other venues.
- The process of teaching, learning, and practicing visualization skills and questions about how we teach, learn, and support learners in individual self-paced learning, peer-learning as well guided by active teaching. The process also includes dedicated teaching materials in the form of, e.g., textbooks, reading lists, activities, cheat sheets, interactive experiences, data sets, and visualization tools.
- Assessment of the visualization education materials and processes as well as the assessment of students, learning objectives, and progress.
The outcomes of the seminar and our discussions aim to have an impact on visualization research and education, education theory and practice, as well as policy making.
Motivation text license Creative Commons BY 4.0
Benjamin Bach, Sheelagh Carpendale, Uta Hinrichs, and Samuel Huron
Classification
- Graphics
- Human-Computer Interaction
- Other Computer Science
Keywords
- Information Visualization
- Visualization Literacy
- Data Literacy
- Education