GraphVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Graph Visualization

Abstract

is a fourth-yeard PhD candidate at the University of Notre Dame working with Dr. Chaoli Wang on High Performance Computing and Scientific Visualization. His main research focus is summarization and reconstruction of big data using GPU-acceleration and deep learning techniques. He has applied his research in isosurface selection for volume visualization and analysis, graph visualization, and is currently using deep learning techniques for analysis of unsteady flow simulations. He has completed a research internship at Argonne National Laboratory in summer 2018. He received his BSc (2014) and MSc (2016) in Software Engineering at the Vienna University of Technology. During his Master's program, he conducted research at the VRVis Research Center in Vienna and continued acquiring experience during a research internship at the University of California, Irvine. Miss Wenqing Chang, Xi'an Jiaotong UniversityWenqing Chang is currently a senior student in Information Engineering from Xi'an Jiaotong University. In 2018, she joined NUS Summer Workshop, developing a 2D webpage game using WebGL and rendering 3D animation using OpenGL. From the fall of 2018 to present, she is a lab researcher in wireless communication, built ambient backscatter enabled secondary communication model and right now is involved in deep learning for joint source-channel coding.

TreeVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Tree Visualization

“…Previously developed educational tools include GraphVisual [7], FlowVisual [13,12], and VolumeVisual [2]. Each tool in the VisVisual library can be used on its own, within the classroom, or used for self-learning.…”

“…We further split the students by their major and level and split the questions by their type and dataset. Table 3 shows the average score and standard deviation for CS (21) and non-CS (5) students and graduate (7) and undergraduate (19) students. We see no significant difference between the groups, which means that TreeVisual is designed sufficiently user-friendly and requires no prior knowledge in CS or other domains.…”