EuroVisEducation

Permanent URI for this community

https://diglib.eg.org/handle/10.2312/3607001

Browse

Now showing 1 - 16 of 16

EuroVis 2024 Education Papers: Frontmatter
(The Eurographics Association, 2024) Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv; Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv
Impacts of Student LLM Usage on Creativity in Data Visualization Education
(The Eurographics Association, 2024) Ahmad, Mak; Ma, Kwan-Liu; Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv
Large language models (LLMs) offer new possibilities for enhancing data visualization education, but the impacts on student experiences remain underexplored. Leveraging tenets of behaviorism, constructivism and experiential learning theories, our mixed-methods study examines LLM integration strategies. We conducted two experiments with different groups of students. The first experiment involved 95 Masters of Business Analytics students who created data narratives based on the Titanic dataset either with or without LLM assistance. The second experiment involved 30 Masters of Information and Data Science students who suggested effective visual encodings for different scenarios with or without LLM assistance in a Viz of the Day activity. We collected quantitative data from surveys and project scores and qualitative data from open-ended responses. Our results show that LLMs can enhance students' ability to create clear, accurate, and effective data stories and visualizations, but they can also pose challenges, such as requiring careful prompt crafting, producing inconsistent or inaccurate outputs, and potentially reducing students' creativity and critical thinking. We discuss how our findings suggest a nuanced balance between LLM guidance and human creativity in data storytelling education and practice, and provide specific directions for future research on LLMs and data visualization.
More Than Chatting: Conversational LLMs for Enhancing Data Visualization Competencies
(The Eurographics Association, 2024) Ahmad, Mak; Ma, Kwan-Liu; Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv
This study investigates the integration of Large Language Models (LLMs) like ChatGPT and Claude into data visualization courses to enhance literacy among computer science students. Through a structured 3-week workshop involving 30 graduate students, we examine the effects of LLM-assisted conversational prompting on students' visualization skills and confidence. Our findings reveal that while engagement and confidence levels increased significantly, improvements in actual visualization proficiency were modest. Our study underscores the importance of prompt engineering skills in maximizing the educational value of LLMs and offers evidence-based insights for software engineering educators on effectively leveraging conversational AI. This research contributes to the ongoing discussion on incorporating AI tools in education, providing a foundation for future ethical and effective LLM integration strategies.
Designing Born-Accessible Courses in Data Science and Visualization: Challenges and Opportunities of a Remote Curriculum Taught by Blind Instructors to Blind Students
(The Eurographics Association, 2024) Seo, JooYoung; O'Modhrain, Sile; Xia, Yilin; Kamath, Sanchita; Lee, Bongshin; Coughlan, James M.; Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv
While recent years have seen a growing interest in accessible visualization tools and techniques for blind people, little attention is paid to the learning opportunities and teaching strategies of data science and visualization tailored for blind individuals. Whereas the former focuses on the accessibility and usability issues of data visualization tools, the latter is concerned with the learnability of concepts and skills for data science and visualization. In this paper, we present novel approaches to teaching data science and visualization to blind students in an online setting. Taught by blind instructors, nine blind learners having a wide range of professional backgrounds participated in a two-week summer course. We describe the course design, teaching strategies, and learning outcomes.We also discuss the challenges and opportunities of teaching data science and visualization to blind students. Our work contributes to the growing body of knowledge on accessible data science and visualization education, and provides insights into the design of online courses for blind students.
Mapping the Landscape of Data Visualizations in Schools and Educational Resources
(The Eurographics Association, 2024) Boucher, Magdalena; Stoiber, Christina; Kejstova, Magdalena; Kandlhofer, Martin; Ertl, Alena; Kriglstein, Simone; Aigner, Wolfgang; Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv
This study explores the use of data visualizations in school education, examining how they are integrated into teaching practices and materials. By conducting semi-structured interviews with 15 teachers across Austria and Slovakia, coupled with a thorough classification of 5,655 data visualizations in 54 Austrian school textbooks, we gained insights into the landscape of visualization types used in educational settings. Despite the discovery of a wide array of visualization types, our analysis reveals a predominant reliance on simple business charts, highlighting a gap in the variety of methods and resources available for effectively teaching a wider range of visualizations. From our research, we derive lessons learned that pave the way for future development of educational methods and materials to enhance visualization literacy in schools.
Vis Repligogy: Towards a Culture of Facilitating Replication Studies in Visualization Pedagogy and Research
(The Eurographics Association, 2024) Syeda, Uzma Haque; South, Laura; Raynor, Justin; Panavas, Liudas; Saffo, David; Morriss, Tommy; Dunne, Cody; Borkin, Michelle A.; Firat, Elif E.; Laramee, Robert S.; Andersen, Nicklas Sindelv
In this paper, we present the Vis Repligogy framework that enables conducting replication studies in the class. Replication studies are crucial to strengthening the data visualization field and ensuring its foundations are solid and methods accurate. Although visualization researchers acknowledge the epistemological significance of replications and their necessity to establish trust and reliability, the field has made little progress to support the publication of such studies and, importantly, provide methods to the community to encourage replications. Therefore, we contribute Vis Repligogy, a novel framework to systematically incorporate replications within visualization course curricula that not only teaches students replication and evaluation methodologies but also results in executed replication studies to validate prior work. To validate the feasibility of the framework, we present case studies of two graduate data visualization courses that implemented it. These courses resulted in a total of five replication studies. Finally, we reflect on our experience implementing the Vis Repligogy framework to provide useful recommendations for future use. We envision this framework will encourage instructors to conduct replications in their courses, help facilitate more replications in visualization pedagogy and in research, and support a culture shift towards reproducible research. Supplemental materials of this paper are available at https://osf.io/ncb6d/.
Lessons from the Pumpkin Patch: Building Community and Visualization Literacy with Physical Visualization
(The Eurographics Association, 2025) Mosca, Ab; Crouser, R. Jordan; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
Teaching introductory visualization classes is a challenging job. These courses often attract students with wide range of prior preparation, and many arrive without formal training in the foundations of computing or statistics. Further, educators face the challenge of growing and adapting in response to new best practices for inclusive and accessible computational education. In this paper, we present a case study documenting a class-wide physical visualization project designed to foster a classroom learning community, reinforce the principle of data-visual mapping, and engage students in a creative and community-focused data project. Guided by inclusive pedagogy and learning science principles of scaffolding, constructivism, and constructionism, the project challenged students to create a physical visualization out of carved pumpkins that would engage the campus community. Student responses to the project were overall extremely positive. An evaluation of the project showed students walked away with increased respect for large-scale projects, a deeper understanding of data-visual mapping, pride and awe in their creation, an increased sense of classroom and campus community, and appreciation for the accessibility of the project.
Engaging Young Minds: Learnings from Data Visualization Workshops with Children and Teenagers
(The Eurographics Association, 2025) Lotteraner, Laura; Schuster, Regina; Staudner, Judith; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
As the role of visual data representations in everyday information consumption is increasing, the importance of teaching data visualization literacy to lay audiences, such as children and teenagers, has grown. Research involving children and teenagers poses unique challenges, resulting in limited literature on teaching data visualization to this audience. This paper reports on the design and implementation of five educational workshops for children and teenagers aged 7 to 16, conducted over three years and teaching data visualization in the context of themes such as climate change, detective work, and social media. The workshops emphasized interactive learning and hands-on projects to engage participants and enhance their understanding of data visualization concepts and critical thinking skills. Key observations include the importance of tailoring content to developmental stages, using storytelling and gamification to sustain interest, and fostering collaboration through activities in small groups. By reflecting on these experiences, the paper contributes to the growing body of research on visualization education and offers practical resources for educators seeking to make data literacy more accessible to younger audiences.
From Reality to Recognition: Evaluating Visualization Analogies for Novice Chart Comprehension
(The Eurographics Association, 2025) Huang, Oliver; Lee, Patrick Yung Kang; Nobre, Carolina; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
Novice learners often have difficulty learning new visualization types because they tend to interpret novel visualizations through the mental models of simpler charts they have previously encountered. Traditional visualization teaching methods, which usually rely on directly translating conceptual aspects of data into concrete data visualizations, often fail to attend to the needs of novice learners navigating this tension. To address this, we conducted an empirical exploration of how analogies can be used to help novices with chart comprehension. We introduced visualization analogies: visualizations that map data structures to real-world contexts to facilitate an intuitive understanding of novel chart types. We evaluated this pedagogical technique using a within-subject study (N=128) where we taught 8 chart types using visualization analogies. Our findings show that visualization analogies improve visual analysis skills and help learners transfer their understanding to actual charts. They effectively introduce visual embellishments, cater to diverse learning preferences, and are preferred by novice learners over traditional chart visualizations. This study offers empirical insights and open-source tools to advance visualization education through analogical reasoning.
LearnClusterVis: A Framework for Clustering-driven Visual Analysis of Programming Learners' Learning Process
(The Eurographics Association, 2025) Bai, Qishuo; Wu, Zhiyuan; Liu, Yinuo; Yang, Yutong; Cao, Junxiang; Dong, Xiaoju; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
The rapid growth of online grading systems (commonly referred to as online judge systems in programming education) provides valuable opportunities to analyze programming learners' processes, but the complexity of such datasets poses significant challenges for instructors lacking specialized analytical techniques. Furthermore, it remains a significant challenge for instructors to effectively identify priority learner groups that require targeted attention and to make informed educational decisions within classroom contexts. To address these challenges, we introduce LearnClusterVis, a clustering-driven visual analysis framework designed to uncover behavioral patterns and developmental trajectories in programming learners' activities. LearnClusterVis is highly extensible and can be applied to various online grading systems. LearnClusterVis leverages learners' submission records to generate customizable visual analysis interfaces, enabling instructors to explore learning patterns, identify learner clusters, monitor progress, deliver personalized interventions, and evaluate the rationality of questions across knowledge domains. The case studies, which implemented the framework using data from two distinct online grading systems, demonstrate its effectiveness and scalability.
VVRT: Virtual Volume Raycaster
(The Eurographics Association, 2025) Wal, Lukke van der; Blesinger, Philip; Kosinka, Jiri; Frey, Steffen; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
Virtual Ray Tracer (VRT) is an educational tool to provide users with an interactive environment for understanding ray-tracing concepts. Extending VRT, we propose Virtual Volume Raycaster (VVRT), an interactive application that allows to view and explore the volume raycasting process in real-time. The goal is to help users-students of scientific visualization and the general public-to better understand the steps of volume raycasting and their characteristics, for example the effect of early ray termination. VVRT shows a scene containing a camera casting rays which interact with a volume. Learners are able to modify and explore various settings, e.g., concerning the transfer function or ray sampling step size. Our educational tool is built with the cross-platform engine Unity, and we make it fully available to be extended and/or adjusted to fit the requirements of courses at other institutions, educational tutorials, or of enthusiasts from the general public. Two user studies demonstrate the effectiveness of VVRT in supporting the understanding and teaching of volume raycasting.
Reflections on Teaching Data-Driven Storytelling at the Journalism School
(The Eurographics Association, 2025) Lan, Xingyu; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
The integration of data visualization in journalism has catalyzed the growth of data storytelling in recent years. Today, it is increasingly common for journalism schools to incorporate data visualization into their curricula. However, the approach to teaching data visualization in journalism schools can diverge significantly from that in computer science or design schools, influenced by the varied backgrounds of students and the distinct value systems inherent to these disciplines. This paper reviews my experience and reflections on teaching data-driven storytelling in a journalism school in Shanghai, China. To begin with, I discuss three prominent characteristics of journalism education (i.e., students' lack of quantitative literacy, the tension between humanism and technocentrism, and the high requirements for content professionalism) that pose challenges for course design and teaching. Then, for each challenge, I share firsthand teaching experiences and discuss corresponding approaches for teaching, such as trying to put visualization into a news context and finding commonality between data-driven storytelling and traditional storytelling. Overall, this paper aims to provide reference and inspiration for instructors who are teaching data visualization and data-driven storytelling to students with non-technical backgrounds.
Exploring the Role of Visualization Tools in Enhancing Computing Education: A Systematic Literature Review
(The Eurographics Association, 2025) Sibia, Naaz; Liut, Michael; Nobre, Carolina; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
Visualization aids in teaching computing by enhancing comprehension and engagement with complex concepts. This systematic literature review analyzes 90 high-quality papers selected from an initial pool of 288 to identify applications, effectiveness, and research gaps in visualization tools for computing education. We categorize tools across domains such as algorithms, programming, online learning, and problem-solving, highlighting their impact on student engagement and learning outcomes. However, we find a lack of rigorous evaluations and a need for specialized visualization models to address specific challenges. Our findings offer actionable insights for educators and researchers to improve teaching methodologies through visual strategies.
EuroVis 2025 Education Papers: Frontmatter
(The Eurographics Association, 2025) Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
DPV (Domain, Purpose, Visual) Framework: A data visualization design pedagogical method for middle schoolers
(The Eurographics Association, 2025) Li, Yixuan; Endert, Alex; Roberts, Jessica; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
Data visualization literacy is essential for K-12 students, yet existing practices emphasize interpreting pre-made visualizations rather than creating them. To address this, we developed the DPV (Domain, Purpose, Visual) framework, which guides middle school students through the visualization design process. The framework simplifies design into three stages: understanding the problem domain, specifying the communication purpose, and translating data into effective visuals. Implemented in a twoweek summer camp as a usage scenario, the DPV framework enabled students to create visualizations addressing community issues. Evaluation of student artifacts, focus group interviews, and surveys demonstrated its effectiveness in enhancing students' design skills and understanding of visualization concepts. This work highlights the DPV framework's potential to foster data visualization literacy for K-12 education and broaden participation in the data visualization community.
Uncertainty Visualization in Medical Education: Utilizing Novel Teaching Technologies to Enhance Clinical Decision-Making
(The Eurographics Association, 2025) Bernards, Ann-Kathrin; Pippow, Andreas; Lang, Tobias; Gillmann, Christina; Aurisano, Jillian; Laramee, Robert S.; Nobre, Carolina
Uncertainty is an inherent aspect of medical decision-making, influencing diagnostics, treatment planning, and prognosis. While uncertainty visualization can aid clinicians in interpreting probabilistic data and supporting shared decision-making with patients, traditional medical education often overlooks data interpretation and visualization training. This gap can hinder clinicians' ability to navigate and communicate complex medical data, potentially affecting patient care. To address this challenge, we developed a structured course that integrates new technologies, hybrid learning models, and practical visualization tools based on generative AI to teach uncertainty visualization effectively. By equipping clinicians with these skills, our approach aims to enhance evidence-based decision-making, improve communication of uncertain data, and ultimately foster better clinical outcomes.

Browse

Browsing EuroVisEducation by Issue Date

Results Per Page

Sort Options