A Didactic Framework for Analyzing Learning Activities to Design InfoVis Courses

Mandy Keck, Elena Stoll, Dietrich Kammer

Research output: Contribution to journalArticlepeer-review


Data visualization is a powerful tool to cope with the demands of our current information age. In order to understand and be able to develop visualizations for specific use cases, data visualization activities (vis activities) have been proposed in recent years. These highly effective tools focus on practical relevance, reflection, and discussion in order to teach data visualization knowledge in a variety of contexts. However, the conscious selection of one or more vis activities for learners in comprehensive courses remains difficult. We aim to support this process by proposing a didactic vis framework. Based on Bloom's revised learning taxonomy, we decompose vis activities into distinct learning activities with their specific learning goals. By assigning the learning goals to the cognitive process and knowledge dimensions, a didactic course structure can be planned and evaluated. To demonstrate this didactic vis framework, we conducted several workshops based on an existing interface construction kit.

Original languageEnglish
Pages (from-to)80-90
Number of pages11
JournalIEEE Computer Graphics and Applications
Issue number6
Early online date1 Oct 2021
Publication statusPublished - 2 Oct 2021


  • Cognitive processes
  • Complexity theory
  • Data visualization
  • Education
  • Taxonomy
  • Tools
  • Visualization
  • Learning
  • Educational Measurement
  • Knowledge


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