IEEE VIS Workshop on Visualization Education, Literacy, and Activities 2024

This is the second IEEE VIS EduVis Workshop on Visualization Education, Literacy, and Activities. This workshop aims to become a forum to share and discuss advances, challenges, and methods at the intersection of visualization and education. The workshop addresses an interdisciplinary audience from and beyond visualization, education, learning analytics, science communication, psychology, or people from adjacent fields such as data science, AI, and HCI. It will include presentations of research papers and working group discussions.

Workshop goals and scope of topics

With this workshop, we want to achieve the following goals:

• build a forum and interdisciplinary community around teaching data visualization, open to researchers, students, and practitioners outside the traditional VIS community
• share research on visualization literacy, education and teaching, and practices
• collect, test, and systematize learning activities
• discuss best practices and challenges concerning visualization education and literacy

Tracks

New this year, are submissions to focus on topics relevant to the EduVIS community. Three general submission tracks for this year’s workshop:

Visualization for Education [Vis4Ed]: use of visualization in educational settings of any discipline or topic

AI for Visualization Education [AI]: integrate or limit tools like ChatGPT and generative AI into visualization education

Generic Topics in Visualization and Education [General]: includes any other submission relevant to the workshop

The workshop topics include, but are not limited to:

• Generative AI and visualization (in learning and assessment)
• Evaluation methods and learning analytics using AI
• Visualization literacy and pedagogy in visualization
• Learning goals and learning methods
• Educational tools
• Visualization activities
• Pedagogy in visualization
• Hybrid and online teaching
• Reflective and research practices
• Understanding audiences
• Guidelines, strategies, and guidance for education
• Debate and discussions on visualization guidelines and well-established knowledge
• Knowledge dissemination
• Challenges and personal experiences
• Informal learning
• Experiential learning (hands-on learning and physicalization)
• Visualizations for public education (e.g., health education, science communication)
• Engagement with visualizations
• Teaching approaches to encourage creativity and design critique
• Accessibility of visualization learning resources

Submission Guidelines and Reviewing Process

The workshop will accept two types of submissions, peer-reviewed by at least two PC members and one workshop organizer.

Paper submissions: full papers (4-8 pages excluding references, must follow the formatting guidelines for VGTC Conference Style Template); submissions will be published at the IEEE Xplore with authors’ permission.

Educator reports: short reports (1-2 pages, template agnostic) to discuss opinions or reflections on teaching experiences or describe the results of a datavis activity conducted and how it could be reused by others and in other contexts; they will be published in the Nightingale magazine (pre-arranged with the Data Visualization Society). This is not intended to be assessed as scientific writing; we recommend framing these reports similar to blog posts. The goal of these reports is to disseminate knowledge to non-academic audiences.

At least one author for each paper or educator report must register and attend the conference in person or virtually.

Important Dates

All deadlines are at 11:59pm (23:59) AoE Anywhere on Earth

• July 1, 2024: Paper and Educator Report Submission
• July 31, 2024: Author Notification
• August 15, 2024: Camera-ready Submission

Program

TBD

Program Committee

TBD

Organizers

General Track

• Fateme Rajabiyazdi, Carleton University
• Mandy Keck, University of Applied Sciences Upper Austria
• Christina Stoiber, St. Pölten University of Applied Sciences
• Jonathan C. Roberts, Bangor University
• Hari Subramonyam, Stanford University
• Lily Ge, Northwestern University
• Magdalena Boucher, St. Pölten University of Applied Sciences
• Benjamin Bach, University of Edinburgh

Vis4Ed Track

• Lonni Besançon, Linkoping University
• Mathis Brossier, Linkoping University
• Anders Ynnerman, Linkoping University
• Konrad Schonborn, Linkoping University

AI Track

• Alon Friedman, University of South Florida
• Bo Pei, University of South Florida
• Ly Dinh, University of South Florida
• Kevin Hawley, University of South Florida
• Julia Woodward, University of South Florida
• Paul Rosen, University of Utah
• Md Dilshadur Rahman, University of Utah
• Yan Chen, University of Virginia Tech