Author(s):
Visualization has become an indispensable means for analyzing data generated from various applications that span many STEM fields. As more and more colleges and universities across the country pay attention to research and education in data science and human-centered computing, adding a new course of Data Visualization into the curricula becomes a growing trend. Following this trend is a significant need for high-quality curriculum materials that can help to teach visualization knowledge and train the STEM workforce for tomorrow. Unfortunately, although visualization research has advanced for 30 years, visualization education has lagged: visualization textbooks only started to emerge in the past decade, and pedagogical software tools that assist the teaching and learning of data visualization are scarce. This project aims to engage students in learning important yet challenging visualization concepts and algorithms by developing the VisVisual toolkit and curriculum materials. Following the learning theories for tool design and classroom pedagogy, the team proposes guiding principles for developing and evaluating VisVisual. The project has delivered four tools (VolumeVisual, FlowVisual, GraphVisual, TreeVisual). Together they cover scalar and vector field visualization in Scientific Visualization and graph and tree drawing in Information Visualization. Our curriculum development complements the toolkit design, resulting in a rich set of materials (datasets, slides, tutorials, videos, quizzes) supporting activity-based learning and problem-based assessment. Many instructors realize the value of developing an interactive software tool for teaching data visualization, yet the time it takes to create such a tool becomes the primary deterrent. Our VisVisual toolkit and associated curriculum materials fill this gap, making it less time-consuming and more convenient for instructors to “use visualization to teach visualization.”
