Data Visualization Literacy
Interactive Pedagogical Tools for Teaching Data Visualization

Theoretical (Analytical):

Practical (Implementation):

Literature Work:


Overview

Nowadays, data visualization is an important competence and there are efforts to start teaching data visualization in elementary school. Given the huge variety and complexity of different visualization techniques additional material might be useful in order to communicate the basic concepts of a certain representation. In this project, we are going to answer the following questions:

  • Which pedagogical tools do exist in order to support lecturers and teachers in educating students about data visualization?
  • What can we do in order to improve the education of data visualization?

Tasks

  • Identify a visualization technique, which is either complex and difficult to understand (like TreeMaps), or has lots of variations (like Scatterplots, Splatterplots, Winglets)
  • Implement the basic visualization technique with its variations.
  • Implement a step by step process to show how the single components are combined in order to create the final visualization.
  • Develop an online prototype to change parameters, show or hide certain visual components or variations of the visualization or some textual description.
  • Implement scenarios/questions/tasks with which students can test their understanding.

Requirements

- Interest in helping lecturers teaching data visualization and students learning about the topic.

- Good programming skills in Java and Javascript.

 

Scope/Duration/Start

  • Scope: Bachelor or Master
  • 6 Month Project, 3 or 6 Month Thesis
  • Start: immediately

Contact

Johannes Fuchs

References

 Treemap Literacy: A Classroom-Based Investigation; The Eurographics Association; 2020
 Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments; Proceedings of the National Academy of Sciences; 2019
 Cheat sheets for data visualization techniques; Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems; 2020