TY - JOUR
T1 - Challenges and Opportunities in Data Visualization Education
T2 - IEEE VIS: Visualization & Visual Analytics
AU - Bach, Benjamin
AU - Keck, Mandy
AU - Rajabiyazdi, Fateme
AU - Losev, Tatiana
AU - Meirelles, Isabel
AU - Dykes, Jason
AU - Laramee, Robert S
AU - AlKadi, Mashael
AU - Stoiber, Christina
AU - Huron, Samuel
AU - Perin, Charles
AU - Morais, Luiz
AU - Aigner, Wolfgang
AU - Kosminsky, Doris
AU - Boucher, Magdalena
AU - Knudsen, Soren
AU - Manataki, Areti
AU - Aerts, Jan
AU - Hinrichs, Uta
AU - Roberts, Jonathan C
AU - Carpendale, Sheelagh
N1 - Publisher Copyright:
© 1995-2012 IEEE.
PY - 2023/11/7
Y1 - 2023/11/7
N2 - This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge. This complex nature leads to a series of interrelated challenges for data visualization education. Driven by a lack of consolidated knowledge, overview, and orientation for visualization education, the 21 authors of this paper-educators and researchers in data visualization-identify and describe 19 challenges informed by our collective practical experience. We organize these challenges around seven themes People, Goals & Assessment, Environment, Motivation, Methods, Materials, and Change. Across these themes, we formulate 43 research questions to address these challenges. As part of our call to action, we then conclude with 5 cross-cutting opportunities and respective action items: embrace DIVERSITY+INCLUSION, build COMMUNITIES, conduct RESEARCH, act AGILE, and relish RESPONSIBILITY. We aim to inspire researchers, educators and learners to drive visualization education forward and discuss why, how, who and where we educate, as we learn to use visualization to address challenges across many scales and many domains in a rapidly changing world: viseducationchallenges.github.io.
AB - This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge. This complex nature leads to a series of interrelated challenges for data visualization education. Driven by a lack of consolidated knowledge, overview, and orientation for visualization education, the 21 authors of this paper-educators and researchers in data visualization-identify and describe 19 challenges informed by our collective practical experience. We organize these challenges around seven themes People, Goals & Assessment, Environment, Motivation, Methods, Materials, and Change. Across these themes, we formulate 43 research questions to address these challenges. As part of our call to action, we then conclude with 5 cross-cutting opportunities and respective action items: embrace DIVERSITY+INCLUSION, build COMMUNITIES, conduct RESEARCH, act AGILE, and relish RESPONSIBILITY. We aim to inspire researchers, educators and learners to drive visualization education forward and discuss why, how, who and where we educate, as we learn to use visualization to address challenges across many scales and many domains in a rapidly changing world: viseducationchallenges.github.io.
KW - Art
KW - Challenges
KW - Creativity
KW - Cultural differences
KW - Data Visualization
KW - Data visualization
KW - Education
KW - Seminars
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85175229487&partnerID=8YFLogxK
U2 - 10.1109/TVCG.2023.3327378
DO - 10.1109/TVCG.2023.3327378
M3 - Article
C2 - 37934634
SN - 1077-2626
VL - 30
SP - 649
EP - 660
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 1
Y2 - 22 October 2023 through 27 October 2023
ER -