Data visualization can be a powerful tool for analyzing and communicating data. However, the overwhelming diversity of options for visualization make it difficult to know how to most effectively visualize data given a specific task. Easel, a visualization recommendation system, was built in response to this problem, specifically for university educators and education support staff looking to improve their visualization techniques of educational data. Its purpose is two-fold:
- Guide a user towards well-formed questions regarding your educational data.
- Provide recommendations for visualizations that will help answer those questions.
The recommended visualizations were created using a design processes and principles outlined in visualization literature, largely from Munzer's Visualization Analysis and Design. We repurposed a visualization selection methodology for the context of education, which can be found by clicking the Selection Process option above along with examples of its usage.
To view the current (development) version of Easel, please visit: shiny.engineering.queensu.ca/easel or using shiny::runGitHub("jkaupp/easel")
The framework underlying sasel was the work of Ajay Sivanand for his Masters of Applied Science degree at Queen's University in Kingston, Ontario, with Dr. Brian Frank. This work was graciously funded by the Higher Education Quality Council of Ontario (HEQCO).
The easel application was collaboratively developed by Dr. Jake Kaupp (Queen's University) building the functional application, with the content aspects of the application being provided by Ajay Sivanand.
Any questions regarding the framework can be directed to Ajay (ajay.sivanand@queensu.ca), any questions about the app can be directed to Jake (jake.kaupp@queensu.ca) and any bugs or issues reported using the issues tab.