Dagstuhl Seminar 22261 - Visualization Empowerment: How to Teach and Learn Data Visualization

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Report from Dagstuhl Seminar 22261 Visualization Empowerment: How to Teach and Learn Data Visualization Benjamin Bach∗1, Sheelagh Carpendale ∗2, Uta Hinrichs ∗3, and Samuel Huron ∗4 Data visualization is becoming an important asset for a data-literate, informed, and critical society. Despite the variety of existing resources to teach theories and practical skills in this domain, little is known about 1) how learning processes in the context of visualization unfold and 2) best practices for engaging and teaching data visualization to diverse audiences and in different contexts. This Dagstuhl Seminar invited practitioners, researchers, and teachers from the areas of visualization, design, education and cognitive psychology to explore these questions from multiple perspectives. Through a range of practical activities, talks, and discussions, we have begun characterizing and classifying teaching methodologies. We have redacted a pedagogical manifesto, and started formalizing the concept of improvisation with visualization in the context of teaching and learning. We have also interrogated creativity as an important aspect of visualization teaching and learning and explored links between data physicalization and visualization teaching activities. Across these different themes, we have begun to map out the challenges of visualization teaching and learning and the opportunities for research and practice in this area.

Jonathan Roberts - Speaker

School of Computer Science & Engineering

Description

Dagstuhl Seminar 22261. Visualization Empowerment: How to Teach and Learn Data Visualization ( Jun 26 – Jul 01, 2022 )

This seminar set out to discuss timely issues and approaches to teaching and education in data visualization. The topic is of growing importance in a world where more and more content is being shared through online news and social media. Our mission as researchers, practitioners and educators in data visualization is to assure quality education for everyone engaging with visualization; this ranges from visualization designers, data scientists, school teachers, journalists, working professionals, students, as well as general public audiences.

26 Jun 2022 → 1 Jul 2022